Complexity

In this paper, we use an algebraic structure quantale and define the idea of fuzzy soft substructures as a generalization of fuzzy substructures in quantale. These fuzzy soft substructures include fuzzy soft subquantales, fuzzy soft ideals, fuzzy soft prime ideals, fuzzy soft semiprime ideals, and fuzzy soft primary ideals. Furthermore, different characterizations of fuzzy soft substructures in quantales are introduced. Moreover, we extend this ideology to investigate that for each fuzzy soft substructure in quantale, there exists an α-soft substructure in quantales. These fuzzy soft subquantales and fuzzy soft ideals are characterized by their level subquantales and ideals, respectively. Finally, fuzzy soft image and fuzzy soft inverse image of fuzzy soft substructures under quantale homomorphism in quantale are discussed.

With the increasing difficulty of conventional oil and gas exploration and development, oil and gas resources have developed from conventional to unconventional, and the exploration and development of tight-oil reservoirs are highly valued. In view of the complexity of the influencing factors of oil-water spontaneous seepage after fracturing and the instability of reservoir recovery, this paper takes the tight sandstone reservoir of Yanchang Formation in the southern Ordos Basin as the research object. Based on the micro-nano pore throat characteristics of tight sandstone, the seepage experiment is carried out, and the theoretical model of seepage suction is constructed. The mechanism and influencing factors of suction and oil displacement after fracturing in tight reservoirs are analyzed. Based on the analysis of fluid buoyancy and gravity, a mathematical model of the oil-water spontaneous flow after fracturing was established, and its influencing factors were analyzed. The experimental results show that the pore throats of tight sandstone are mainly in micron- and submicron scale, and the reservoir permeability is related to the pore throat structure, oil-water interfacial tension, and wettability. After fracturing, with the increase of the fracture length, the seepage velocity gradually decreases. With the increase of fracture opening, the influence of buoyancy and gravity on seepage velocity increases. With the increase of the fracture number, seepage velocity also increases. The fracture helps to reduce the adsorption of oil droplets on the core surface and improve the efficiency of spontaneous imbibition and oil displacement of the core. The research results provide theoretical data support for enhancing oil recovery and have important application guiding significance for the operational reliability of manufacturing systems with complex topology and the complexity and operability of production operations in manufacturing systems.

The mining of key nodes is an important topic in complex network research, which can help identify influencers. The study is necessary for blocking the spread of epidemics, controlling public opinion, and managing transportation. The techniques thus far suggested have a lot of drawbacks; they either depend on the regional distribution of nodes or the global character of the network. The gravity formula based on node information is a good mathematical model that can represent the magnitude of attraction between nodes. However, the gravity model requires less node information and has limitations. In this study, we propose a gravity model based on Shannon entropy to effectively address the aforementioned issues. The spreading probability method is employed to enhance the model’s functionality and applicability. Through testing, it has been determined that the suggested model is a good alternative to the gravity model for selecting influential nodes.

Powder bed fusion (PBF) applies to various metallic materials used in the metal printing process of building a wide range of complex parts compared to other AM technologies. PBF process has several variants such as DMLS (direct metal laser sintering), EBM (electron beam melting), SHS (selective heat sintering), SLM (selective laser melting), and SLS (selective laser sintering). For PBF to reach its maximum potential, machine learning (ML) algorithms are used with suitable materials to achieve goals cost-effectively. Various applications of neural networks, including ANNs, CNNs, RNNs, and other popular techniques such as KNN, SVM, and GP were reviewed, and future challenges were discussed. Some special-purpose algorithms were listed as follows: GAN, SeDANN, SCNN, K-means, PCA, etc. This review presents the evolution, current status, challenges, and prospects of these technologies in terms of material, features, process parameters, applications, advantages, disadvantages, etc., to explain their significance and provide an in-depth understanding of the same.

This paper presents the design of an adaptive controller that solves the synchronization control problem of two identical Nwachioma chaotic systems in a master-slave configuration. The closed-loop stability is guaranteed by means of a Lyapunov-like analysis. With the aim of verifying the feasibility and performance of the proposed approach, a comparison with an active control algorithm is developed at the numerical simulation level. Based on such results, the master-slave Nwachioma chaotic system in closed-loop with adaptive control is now being experimentally tested by using two personal computers and two low-cost Arduino UNO boards. The experimental results not only show the good performance of the adaptive control but also that Arduino UNO boards are an excellent option for the experimental setup.

The goal of this study is to suggest a new general triple integral transform known as Gamar transform. Next, we compare the current transform to a number of existing triple integral transforms such as those by Laplace, Sumudu, Elzaki, Aboodh, and Laplace–Aboodh–Sumudu. We outline its essential properties and prove some important results, including linearity property, existence theorem, triple convolution theorem, and derivatives properties. Moreover, the proposed new transform is applied to solve some partial differential equations (PDEs) such as Laplace, Mboctara, and Wave equations. The capacity of general triple integral transforms to change PDEs into simple algebraic equations is demonstrated.