Mathematical Problems in Engineering The latest articles from Hindawi Publishing Corporation © 2014 , Hindawi Publishing Corporation . All rights reserved. A New Dataset Size Reduction Approach for PCA-Based Classification in OCR Application Thu, 17 Apr 2014 15:02:30 +0000 A major problem of pattern recognition systems is due to the large volume of training datasets including duplicate and similar training samples. In order to overcome this problem, some dataset size reduction and also dimensionality reduction techniques have been introduced. The algorithms presently used for dataset size reduction usually remove samples near to the centers of classes or support vector samples between different classes. However, the samples near to a class center include valuable information about the class characteristics and the support vector is important for evaluating system efficiency. This paper reports on the use of Modified Frequency Diagram technique for dataset size reduction. In this new proposed technique, a training dataset is rearranged and then sieved. The sieved training dataset along with automatic feature extraction/selection operation using Principal Component Analysis is used in an OCR application. The experimental results obtained when using the proposed system on one of the biggest handwritten Farsi/Arabic numeral standard OCR datasets, Hoda, show about 97% accuracy in the recognition rate. The recognition speed increased by 2.28 times, while the accuracy decreased only by 0.7%, when a sieved version of the dataset, which is only as half as the size of the initial training dataset, was used. Mohammad Amin Shayegan and Saeed Aghabozorgi Copyright © 2014 Mohammad Amin Shayegan and Saeed Aghabozorgi. All rights reserved. A Systematic Evaluation Model for Solar Cell Technologies Thu, 17 Apr 2014 15:00:03 +0000 Fossil fuels, including coal, petroleum, natural gas, and nuclear energy, are the primary electricity sources currently. However, with depletion of fossil fuels, global warming, nuclear crisis, and increasing environmental consciousness, the demand for renewable energy resources has skyrocketed. Solar energy is one of the most popular renewable energy resources for meeting global energy demands. Even though there are abundant studies on various solar technology developments, there is a lack of studies on solar technology evaluation and selection. Therefore, this research develops a model using interpretive structural modeling (ISM), benefits, opportunities, costs, and risks concept (BOCR), and fuzzy analytic network process (FANP) to aggregate experts' opinions in evaluating current available solar cell technology. A case study in a photovoltaics (PV) firm is used to examine the practicality of the proposed model in selecting the most suitable technology for the firm in manufacturing new products. Chang-Fu Hsu, Rong-Kwei Li, He-Yau Kang, and Amy H. I. Lee Copyright © 2014 Chang-Fu Hsu et al. All rights reserved. A Real-Time Location-Based Services System Using WiFi Fingerprinting Algorithm for Safety Risk Assessment of Workers in Tunnels Thu, 17 Apr 2014 14:59:11 +0000 This paper investigates the feasibility of a real-time tunnel location-based services (LBS) system to provide workers’ safety protection and various services in concrete dam site. In this study, received signal strength- (RSS-) based location using fingerprinting algorithm and artificial neural network (ANN) risk assessment is employed for position analysis. This tunnel LBS system achieves an online, real-time, intelligent tracking identification feature, and the on-site running system has many functions such as worker emergency call, track history, and location query. Based on ANN with a strong nonlinear mapping, and large-scale parallel processing capabilities, proposed LBS system is effective to evaluate the risk management on worker safety. The field implementation shows that the proposed location algorithm is reliable and accurate (3 to 5 meters) enough for providing real-time positioning service. The proposed LBS system is demonstrated and firstly applied to the second largest hydropower project in the world, to track workers on tunnel site and assure their safety. The results show that the system is simple and easily deployed. Peng Lin, Qingbin Li, Qixiang Fan, Xiangyou Gao, and Senying Hu Copyright © 2014 Peng Lin et al. All rights reserved. Guaranteed Cost Control for Multirate Networked Control Systems with Both Time-Delay and Packet-Dropout Thu, 17 Apr 2014 14:03:55 +0000 Compared with traditional networked control systems, the sampling rates of the nodes are not the same in the multirate networked control systems (NCSs). This paper presents a new stabilization method for multirate NCSs. A multirate NCSs with simultaneous considering time-delay and packet-dropout is modeled as a time-varying sampling system with time-delay. The proposed Lyapunov function deceases at each input signal updating point, which is largely ignored in prior works. Sufficient condition for the stochastic mean-square stability of the multirate NCSs is given, and the cost function value is less than a bound. Numerical examples are presented to illustrate the effectiveness of the proposed control scheme. Qixin Zhu, Binbin Xie, and Yonghong Zhu Copyright © 2014 Qixin Zhu et al. All rights reserved. Nonlinear Finite Strain Consolidation Analysis with Secondary Consolidation Behavior Thu, 17 Apr 2014 14:01:23 +0000 This paper aims to analyze nonlinear finite strain consolidation with secondary consolidation behavior. On the basis of some assumptions about the secondary consolidation behavior, the continuity equation of pore water in Gibson’s consolidation theory is modified. Taking the nonlinear compressibility and nonlinear permeability of soils into consideration, the governing equation for finite strain consolidation analysis is derived. Based on the experimental data of Hangzhou soft clay samples, the new governing equation is solved with the finite element method. Afterwards, the calculation results of this new method and other two methods are compared. It can be found that Gibson’s method may underestimate the excess pore water pressure during primary consolidation. The new method which takes the secondary consolidation behavior, the nonlinear compressibility, and nonlinear permeability of soils into consideration can precisely estimate the settlement rate and the final settlement of Hangzhou soft clay sample. Jieqing Huang, Xinyu Xie, Jifa Zhang, Jinzhu Li, and Wenjun Wang Copyright © 2014 Jieqing Huang et al. All rights reserved. Traffic Incident Clearance Time and Arrival Time Prediction Based on Hazard Models Thu, 17 Apr 2014 13:45:05 +0000 Accurate prediction of incident duration is not only important information of Traffic Incident Management System, but also an effective input for travel time prediction. In this paper, the hazard based prediction models are developed for both incident clearance time and arrival time. The data are obtained from the Queensland Department of Transport and Main Roads’ STREAMS Incident Management System (SIMS) for one year ending in November 2010. The best fitting distributions are drawn for both clearance and arrival time for 3 types of incident: crash, stationary vehicle, and hazard. The results show that Gamma, Log-logistic, and Weibull are the best fit for crash, stationary vehicle, and hazard incident, respectively. The obvious impact factors are given for crash clearance time and arrival time. The quantitative influences for crash and hazard incident are presented for both clearance and arrival. The model accuracy is analyzed at the end. Yang beibei Ji, Rui Jiang, Ming Qu, and Edward Chung Copyright © 2014 Yang beibei Ji et al. All rights reserved. Exchange Rate Forecasting Using Entropy Optimized Multivariate Wavelet Denoising Model Thu, 17 Apr 2014 13:43:47 +0000 Exchange rate is one of the key variables in the international economics and international trade. Its movement constitutes one of the most important dynamic systems, characterized by nonlinear behaviors. It becomes more volatile and sensitive to increasingly diversified influencing factors with higher level of deregulation and global integration worldwide. Facing the increasingly diversified and more integrated market environment, the forecasting model in the exchange markets needs to address the individual and interdependent heterogeneity. In this paper, we propose the heterogeneous market hypothesis- (HMH-) based exchange rate modeling methodology to model the micromarket structure. Then we further propose the entropy optimized wavelet-based forecasting algorithm under the proposed methodology to forecast the exchange rate movement. The multivariate wavelet denoising algorithm is used to separate and extract the underlying data components with distinct features, which are modeled with multivariate time series models of different specifications and parameters. The maximum entropy is introduced to select the best basis and model parameters to construct the most effective forecasting algorithm. Empirical studies in both Chinese and European markets have been conducted to confirm the significant performance improvement when the proposed model is tested against the benchmark models. Kaijian He, Lijun Wang, Yingchao Zou, and Kin Keung Lai Copyright © 2014 Kaijian He et al. All rights reserved. The Optimization Problems of Transmit and Receive Design for Radar Operating in Littoral Zones Thu, 17 Apr 2014 13:09:43 +0000 The complex environments of the littoral zones prevent the radar from operating efficiently. We propose a waveform and filter design approach to help the radar improve the performance in littoral zones. The approach includes a phase-only nonlinear programming method for suppressing correlation sidelobes in specified Doppler and range intervals, and an alternating projection based algorithm for designing receive filters. Several numerical examples are provided to demonstrate the usage and effectiveness of the proposed methods. Yi-nan Zhao, Feng-cong Li, and Zhi-quan Zhou Copyright © 2014 Yi-nan Zhao et al. All rights reserved. Hierarchical MPC Secondary Control for Electric Power System Thu, 17 Apr 2014 13:06:06 +0000 Although in electric power systems (EPS) the regulatory level guarantees a bounded error between the reference and the corresponding system variables, to keep its availability in time, optimizing the system operation is required for operational reasons such as, economic and/or environmental. In order to do this, there are the following alternative solutions: first, replacing the regulatory system with an optimized control system or simply adding an optimized supervisory level, without modifying the regulatory level. However, due to the high cost associated with the modification of regulatory controllers, the industrial sector accepts more easily the second alternative. In addition, a hierarchical supervisory control system improves the regulatory level through a new optimal signal support, without any direct intervention in the already installed regulatory control system. This work presents a secondary frequency control scheme in an electric power system, through a hierarchical model predictive control (MPC). The regulatory level, corresponding to traditional primary and secondary control, will be maintained. An optimal additive signal is included, which is generated from a MPC algorithm, in order to optimize the behavior of the traditional secondary control system. Freddy Milla, Manuel A. Duarte-Mermoud, and Noreys Aguila-Camacho Copyright © 2014 Freddy Milla et al. All rights reserved. Comparison of Three Different Curves Used in Path Planning Problems Based on Particle Swarm Optimizer Thu, 17 Apr 2014 13:03:52 +0000 In path planning problems, the most important task is to find a suitable collision-free path which satisfies some certain criteria (the shortest path length, security, feasibility, smoothness, and so on), so defining a suitable curve to describe path is essential. Three different commonly used curves are compared and discussed based on their performance on solving a set of path planning problems. Dynamic multiswarm particle swarm optimizer is employed to optimize the necessary parameters for these curves. The results show that Bezier curve is the most suitable curve for producing path for the certain path planning problems discussed in this paper. Safety criterion is considered as a constrained condition. A new constraint handling method is proposed and compared with other two constraint handling methods. The results show that the new method has a better characteristic to improve the performance of algorithm. J. J. Liang, H. Song, B. Y. Qu, and Z. F. Liu Copyright © 2014 J. J. Liang et al. All rights reserved. Stress Analysis of Gear Meshing Impact Based on SPH Method Thu, 17 Apr 2014 13:00:57 +0000 Based on the kinetic equations of the gear mesh impact, SPH discrete equations were established. Numerical simulation was carried out on the meshing impact process of the gear, and stress and strain of each discrete point were obtained. After data processing, stress propagation was calculated, which shows stress distribution on tooth-profile surface. It is concluded that the stress concentrate mainly occurs in the pitch circle. The paper provides an effective new numerical simulation algorithm to gear mechanical properties analysis. Rahmatjan Imin and Mamtimin Geni Copyright © 2014 Rahmatjan Imin and Mamtimin Geni. All rights reserved. Valuing Catastrophe Bonds Involving Credit Risks Thu, 17 Apr 2014 12:22:02 +0000 Catastrophe bonds are the most important products in catastrophe risk securitization market. For the operating mechanism, CAT bonds may have a credit risk, so in this paper we consider the influence of the credit risk on CAT bonds pricing that is different from the other literature. We employ the Jarrow and Turnbull method to model the credit risks and get access to the general pricing formula using the Extreme Value Theory. Furthermore, we present an empirical pricing study of the Property Claim Services data, where the parameters in the loss function distribution are estimated by the MLE method and the default probabilities are deduced by the US financial market data. Then we get the catastrophe bonds value by the Monte Carlo method. Jian Liu, Jihong Xiao, Lizhao Yan, and Fenghua Wen Copyright © 2014 Jian Liu et al. All rights reserved. Attitude Analysis and Robust Adaptive Backstepping Sliding Mode Control of Spacecrafts Orbiting Irregular Asteroids Thu, 17 Apr 2014 10:06:14 +0000 Attitude stability analysis and robust control algorithms for spacecrafts orbiting irregular asteroids are investigated in the presence of model uncertainties and external disturbances. Rigid spacecraft nonlinear attitude models are considered and detailed attitude stability analysis of spacecraft subjected to the gravity gradient torque in an irregular central gravity field is included in retrograde orbits and direct orbits using linearized system model. The robust adaptive backstepping sliding mode control laws are designed to make the attitude of the spacecrafts stabilized and responded accurately to the expectation in the presence of disturbances and parametric uncertainties. Numerical simulations are included to illustrate the spacecraft performance obtained using the proposed control laws. Chunhui Liang and Yuanchun Li Copyright © 2014 Chunhui Liang and Yuanchun Li. All rights reserved. Novel Particle Swarm Optimization and Its Application in Calibrating the Underwater Transponder Coordinates Thu, 17 Apr 2014 08:08:54 +0000 A novel improved particle swarm algorithm named competition particle swarm optimization (CPSO) is proposed to calibrate the Underwater Transponder coordinates. To improve the performance of the algorithm, TVAC algorithm is introduced into CPSO to present an extension competition particle swarm optimization (ECPSO). The proposed method is tested with a set of 10 standard optimization benchmark problems and the results are compared with those obtained through existing PSO algorithms, basic particle swarm optimization (BPSO), linear decreasing inertia weight particle swarm optimization (LWPSO), exponential inertia weight particle swarm optimization (EPSO), and time-varying acceleration coefficient (TVAC). The results demonstrate that CPSO and ECPSO manifest faster searching speed, accuracy, and stability. The searching performance for multimodulus function of ECPSO is superior to CPSO. At last, calibration of the underwater transponder coordinates is present using particle swarm algorithm, and novel improved particle swarm algorithm shows better performance than other algorithms. Zheping Yan, Chao Deng, Benyin Li, and Jiajia Zhou Copyright © 2014 Zheping Yan et al. All rights reserved. An Agent-Based Computational Model for China’s Stock Market and Stock Index Futures Market Thu, 17 Apr 2014 07:42:21 +0000 This study presents an agent-based computational cross market model for Chinese equity market structure, which includes both stocks and CSI 300 index futures. In this model, we design several stocks and one index future to simulate this structure. This model allows heterogeneous investors to make investment decisions with restrictions including wealth, market trading mechanism, and risk management. Investors’ demands and order submissions are endogenously determined. Our model successfully reproduces several key features of the Chinese financial markets including spot-futures basis distribution, bid-ask spread distribution, volatility clustering, and long memory in absolute returns. Our model can be applied in cross market risk control, market mechanism design, and arbitrage strategies analysis. Hai-Chuan Xu, Wei Zhang, Xiong Xiong, and Wei-Xing Zhou Copyright © 2014 Hai-Chuan Xu et al. All rights reserved. An Empirical Study of the Effect of Investor Sentiment on Returns of Different Industries Thu, 17 Apr 2014 07:18:20 +0000 Studies on investor sentiment are mostly focused on the stock market, but little attention has been paid to the effect of investor sentiment on the return of a specific industry. This paper constructs a proxy variable to examine the relationship between investor sentiment and the return of a specific industry, using the Principle Component Analysis, and finds that investor sentiment is positively correlated with the industry return of the current period and negatively correlated with that of one lag period; we classify investor sentiment as optimistic state and pessimistic state and find that optimistic investor sentiment has a positive effect on stock returns of most industries, while pessimistic investor sentiment has no effect on them; this paper further builds a two-state Markov regime switching model and finds that sentiment has different effect on different industries returns on different states of market. Chuangxia Huang, Xin Yang, Xiaoguang Yang, and Hu Sheng Copyright © 2014 Chuangxia Huang et al. All rights reserved. Exact Solutions for -Dimensional Nonlinear Fokas Equation Using Extended F-Expansion Method and Its Variant Thu, 17 Apr 2014 06:46:21 +0000 The construction of exact solution for higher-dimensional nonlinear equation plays an important role in knowing some facts that are not simply understood through common observations. In our work, -dimensional nonlinear Fokas equation, which is an important physical model, is discussed by using the extended F-expansion method and its variant. And some new exact solutions expressed by Jacobi elliptic function, Weierstrass elliptic function, hyperbolic function, and trigonometric function are obtained. The related results are enriched. Yinghui He Copyright © 2014 Yinghui He. All rights reserved. Sensitivity Analysis of Deviation Source for Fast Assembly Precision Optimization Thu, 17 Apr 2014 06:22:12 +0000 Assembly precision optimization of complex product has a huge benefit in improving the quality of our products. Due to the impact of a variety of deviation source coupling phenomena, the goal of assembly precision optimization is difficult to be confirmed accurately. In order to achieve optimization of assembly precision accurately and rapidly, sensitivity analysis of deviation source is proposed. First, deviation source sensitivity is defined as the ratio of assembly dimension variation and deviation source dimension variation. Second, according to assembly constraint relations, assembly sequences and locating, deviation transmission paths are established by locating the joints between the adjacent parts, and establishing each part’s datum reference frame. Third, assembly multidimensional vector loops are created using deviation transmission paths, and the corresponding scalar equations of each dimension are established. Then, assembly deviation source sensitivity is calculated by using a first-order Taylor expansion and matrix transformation method. Finally, taking assembly precision optimization of wing flap rocker as an example, the effectiveness and efficiency of the deviation source sensitivity analysis method are verified. Jianjun Tang, Xitian Tian, and Junhao Geng Copyright © 2014 Jianjun Tang et al. All rights reserved. Mixed Convection Unsteady Stagnation-Point Flow towards a Stretching Sheet with Slip Effects Thu, 17 Apr 2014 00:00:00 +0000 The paper studies the unsteady mixed convection flow of an incompressible viscous fluid about a stagnation point on a stretching sheet in presence of velocity and thermal slips. The governing equations are transformed into the ordinary differential equations by using similarity transformations. The transformed equations are solved numerically by an efficient shooting method. The characteristics of the flow and heat transfer features for governing parameters are analyzed and discussed for both the assisting and opposing flows. It is found that dual solutions exist for certain range of buoyancy parameter which again depend on the unsteadiness parameter and the slip parameters (i.e., and ). The numerical results show that the increase of unsteadiness parameter and the slip effects cause increment in the existence range of similarity solution. The effects of unsteadiness parameter, the velocity ratio parameter, and the velocity and thermal slip parameters on the velocity and temperature distributions are analyzed and discussed. Hui Chen Copyright © 2014 Hui Chen. All rights reserved. Preserving Global Exponential Stability of Hybrid BAM Neural Networks with Reaction Diffusion Terms in the Presence of Stochastic Noise and Connection Weight Matrices Uncertainty Thu, 17 Apr 2014 00:00:00 +0000 We study the impact of stochastic noise and connection weight matrices uncertainty on global exponential stability of hybrid BAM neural networks with reaction diffusion terms. Given globally exponentially stable hybrid BAM neural networks with reaction diffusion terms, the question to be addressed here is how much stochastic noise and connection weights matrices uncertainty the neural networks can tolerate while maintaining global exponential stability. The upper threshold of stochastic noise and connection weights matrices uncertainty is defined by using the transcendental equations. We find that the perturbed hybrid BAM neural networks with reaction diffusion terms preserve global exponential stability if the intensity of both stochastic noise and connection weights matrices uncertainty is smaller than the defined upper threshold. A numerical example is also provided to illustrate the theoretical conclusion. Yan Li and Yi Shen Copyright © 2014 Yan Li and Yi Shen. All rights reserved. A Joint Optimization of Momentum Item and Levenberg-Marquardt Algorithm to Level Up the BPNN’s Generalization Ability Wed, 16 Apr 2014 17:24:13 +0000 Back propagation neural network (BPNN) as a kind of artificial neural network is widely used in pattern recognition and trend prediction. For standard BPNN, it has many drawbacks such as trapping into local optima, oscillation, and long training time. Because training the standard BPNN is based on gradient descent method, and the learning rate is fixed. Momentum item and Levenberg-Marquardt (LM) algorithm are two ways to adjust the weights among the neurons and improve the BPNN’s performance. However, there is still much space to improve the two algorithms. The hybrid optimization of damping factor of LM and the dynamic momentum item is proposed in this paper. The improved BPNN is validated by Fisher Iris data and wine data. Then, it is used to predict the visit_spend. The database is provided by Dunnhumby's Shopper Challenge. Compared with the other two improved BPNNs, the proposed method gets a better performance. Therefore, the proposed method can be used to do the pattern recognition and time series prediction more effectively. Lei Xiao, Xiaohui Chen, and Xinghui Zhang Copyright © 2014 Lei Xiao et al. All rights reserved. Wind Turbine Gearbox Fault Diagnosis Method Based on Riemannian Manifold Wed, 16 Apr 2014 17:19:46 +0000 As multivariate time series problems widely exist in social production and life, fault diagnosis method has provided people with a lot of valuable information in the finance, hydrology, meteorology, earthquake, video surveillance, medical science, and other fields. In order to find faults in time sequence quickly and efficiently, this paper presents a multivariate time series processing method based on Riemannian manifold. This method is based on the sliding window and uses the covariance matrix as a descriptor of the time sequence. Riemannian distance is used as the similarity measure and the statistical process control diagram is applied to detect the abnormity of multivariate time series. And the visualization of the covariance matrix distribution is used to detect the abnormity of mechanical equipment, leading to realize the fault diagnosis. With wind turbine gearbox faults as the experiment object, the fault diagnosis method is verified and the results show that the method is reasonable and effective. Shoubin Wang, Xiaogang Sun, and Chengwei Li Copyright © 2014 Shoubin Wang et al. All rights reserved. A Novel Improved ELM Algorithm for a RealIndustrial Application Wed, 16 Apr 2014 16:10:49 +0000 It is well known that the feedforward neural networks meet numbers of difficulties in the applications because of its slow learning speed. The extreme learning machine (ELM) is a new single hidden layer feedforward neural network method aiming at improving the training speed. Nowadays ELM algorithm has received wide application with its good generalization performance under fast learning speed. However, there are still several problems needed to be solved in ELM. In this paper, a new improved ELM algorithm named R-ELM is proposed to handle the multicollinear problem appearing in calculation of the ELM algorithm. The proposed algorithm is employed in bearing fault detection using stator current monitoring. Simulative results show that R-ELM algorithm has better stability and generalization performance compared with the original ELM and the other neural network methods. Hai-Gang Zhang, Sen Zhang, and Yi-Xin Yin Copyright © 2014 Hai-Gang Zhang et al. All rights reserved. Wind Turbine Pitch Control and Load Mitigation Using an Adaptive Approach Wed, 16 Apr 2014 14:21:43 +0000 We present an application of adaptive output feedback control design to wind turbine collective pitch control and load mitigation. Our main objective is the design of an output feedback controller without wind speed estimation, ensuring that the generator speed tracks the reference trajectory with robustness to uncertain parameters and time-varying disturbances (mainly the uniform wind disturbance across the wind turbine rotor). The wind turbine model CART (controls advanced research turbine) developed by the national renewable energy laboratory (NREL) is used to validate the performance of the proposed adaptive controller using the FAST (fatigue, aerodynamics, structures, and turbulence) code. A comparative study is also conducted between the proposed controller and the most popular methods in practice: gain scheduling PI (GSPI) controls and disturbance accommodating control (DAC) methods. The results show better performance of output feedback controller over the other two methods. Moreover, based on the FAST software and LQR analysis in the reference model selection of adaptive controller, tradeoff can be achieved between control performance and loads mitigation. Danyong Li, Yongduan Song, Wenchuan Cai, Peng Li, and Hamid R. Karimi Copyright © 2014 Danyong Li et al. All rights reserved. The Research on Modeling and Simulation of TFE Polymerization Process Wed, 16 Apr 2014 14:15:13 +0000 PTFE (polytetrafluoroethylene) is the fluorinated straight-chain polymer, made by the polymerization of tetrafluoroethylene monomer; it is used widely because of its excellent performance and can be obtained by the polymerization of body, solutions, suspensions, and emulsions. But only the last two are the main ways. This research paper makes simulation based on Polymer Plus. It uses the emulsion polymerization method at background to carry out a semibatch reactor system. Upon the actual production conditions, simulation process under the steady state conditions is used to analyze the effects of the changes on operating conditions; the corresponding dynamic model is created to analyze the impact of the changes of conditions on the entire system. Moreover, the amount of APS which plays an important part in this reaction is discussed for getting the most suitable amount of initiator. Because of less research work on this job, it is so difficult to find the related data from the literature. Therefore, this research will have a great significance for the process of the tetrafluoroethylene emulsion polymerization in the future. Jing Gao Sun and Qin Cao Copyright © 2014 Jing Gao Sun and Qin Cao. All rights reserved. Improved Artificial Bee Colony Algorithm and Its Application in LQR Controller Optimization Wed, 16 Apr 2014 14:12:42 +0000 In order to get the optimal performance of controller and improve the design efficiency, artificial bee colony (ABC) algorithm as a metaheuristic approach which is inspired by the collective foraging behavior of honey bee swarms is considered for optimal linear quadratic regulator (LQR) design in this paper. Furthermore, for accelerating the convergence speed and enhancing the diversities of population of the traditional ABC algorithm, improved solution searching approach is proposed creatively. The proposed approach refers to the procedure of differential mutation in differential evolutionary (DE) algorithm and produces uniform distributed food sources in employed bee phase to avoid local optimal solution. Meanwhile, during the onlooker bees searching stage where the solution search area has been narrowed by employed bees, new solutions are generated around the solution with higher fitness value to keep the fitness values increasing monotonously. The improved ABC algorithm is applied to the optimization of LQR controller for the circular-rail double inverted pendulum system, and the simulation results show the effect on the proposed optimization problem. Haiquan Wang, Lei Liao, Dongyun Wang, Shengjun Wen, and Mingcong Deng Copyright © 2014 Haiquan Wang et al. All rights reserved. Almost Sure Asymptotical Adaptive Synchronization for Neutral-Type Neural Networks with Stochastic Perturbation and Markovian Switching Wed, 16 Apr 2014 12:59:31 +0000 The problem of almost sure (a.s.) asymptotic adaptive synchronization for neutral-type neural networks with stochastic perturbation and Markovian switching is researched. Firstly, we proposed a new criterion of a.s. asymptotic stability for a general neutral-type stochastic differential equation which extends the existing results. Secondly, based upon this stability criterion, by making use of Lyapunov functional method and designing an adaptive controller, we obtained a condition of a.s. asymptotic adaptive synchronization for neutral-type neural networks with stochastic perturbation and Markovian switching. The synchronization condition is expressed as linear matrix inequality which can be easily solved by Matlab. Finally, we introduced a numerical example to illustrate the effectiveness of the method and result obtained in this paper. Wuneng Zhou, Xueqing Yang, Jun Yang, Anding Dai, and Huashan Liu Copyright © 2014 Wuneng Zhou et al. All rights reserved. Stability Analysis of Fractional-Order Nonlinear Systems with Delay Wed, 16 Apr 2014 12:55:49 +0000 Stability analysis of fractional-order nonlinear systems with delay is studied. We propose the definition of Mittag-Leffler stability of time-delay system and introduce the fractional Lyapunov direct method by using properties of Mittag-Leffler function and Laplace transform. Then some new sufficient conditions ensuring asymptotical stability of fractional-order nonlinear system with delay are proposed firstly. And the application of Riemann-Liouville fractional-order systems is extended by the fractional comparison principle and the Caputo fractional-order systems. Numerical simulations of an example demonstrate the universality and the effectiveness of the proposed method. Yu Wang and Tianzeng Li Copyright © 2014 Yu Wang and Tianzeng Li. All rights reserved. Allocating Tradable Emissions Permits Based on the Proportional Allocation Concept to Achieve a Low-Carbon Economy Wed, 16 Apr 2014 11:53:49 +0000 A key issue within the emissions trading system is how tradable emissions permits (TEPs) are initially allocated among a set of entities. This study proposes an approach based on the proportional allocation concept to allocate TEPs among a set of decision making units (DMUs). We firstly deduce a TEP allocation set based on the rule that the TEPs allocated to DMUs should be proportional to their environmental contribution. We then obtain the allocation intervals of DMUs from the set, expressing the allocation as the convex combination between the upper and the lower bound. Finally, we define the satisfaction degree as the coefficient of the convex combination, and propose an algorithm based on the max-min fairness of satisfaction degrees to obtain a unique TEP allocation plan. To illustrate our approach, we provide the example of how TEPs are allocated among 30 provincial administrative regions in China. Our findings indicate that our allocation method can be helpful for achieving a saving in energy consumption and reducing emissions. In addition, from the data envelopment analysis perspective, the TEP allocation set can ensure that both each individual DMU and the organization as a whole become efficient under a common set of variable weights. Qianzhi Dai, Yongjun Li, Qiwei Xie, and Liang Liang Copyright © 2014 Qianzhi Dai et al. All rights reserved. Portfolio Selection with Subsistence Consumption Constraints and CARA Utility Wed, 16 Apr 2014 11:51:34 +0000 We consider the optimal consumption and portfolio choice problem with constant absolute risk aversion (CARA) utility and a subsistence consumption constraint. A subsistence consumption constraint means there exists a positive constant minimum level for the agent’s optimal consumption. We use the dynamic programming approach to solve the optimization problem and also give the verification theorem. We illustrate the effects of the subsistence consumption constraint on the optimal consumption and portfolio choice rules by the numerical results. Gyoocheol Shim and Yong Hyun Shin Copyright © 2014 Gyoocheol Shim and Yong Hyun Shin. All rights reserved.