Mathematical Problems in Engineering

Advanced Intelligent Fuzzy Systems Modeling Technologies for Smart Cities


Publishing date
01 Nov 2021
Status
Published
Submission deadline
18 Jun 2021

Lead Editor

1Jiangnan University, Wuxi, China

2Persian Gulf University, Bushehr, Iran

3Tongji University, Shanghai, China


Advanced Intelligent Fuzzy Systems Modeling Technologies for Smart Cities

Description

Smart cities constitute a new generation of information technology, considering Internet of Things (IoT), cloud computing, big data, and artificial intelligence (AI), which are fully used in all fields of life in the city. Based on comprehensive and thorough perception, wide-band ubiquitous interconnection, and intelligent integration of advanced forms of urban informationization, the deep integration of informationization, industrialisation, and urbanisation can be achieved. This can then alleviate the "big city disease" by improving the quality of urbanisation, realising fine and dynamic management, improving the effectiveness of urban management, and improving the quality of life of citizens. However, in the process of promoting smart cities, there are many challenges and opportunities to be solved urgently.

In particular, advanced intelligent fuzzy systems (AIFS) have found numerous successful applications in diverse fields, including infrastructure deployment and control, garbage sorting and recycling, traffic congestion prediction and dredging, smart medical and health monitoring, emergency disaster and first aid, smart city communication, and smart power transmission. Recently, design frameworks and diversity applications of AIFS have been investigated to cope with future smart cities, which have shown great potential in fuzzy multi-criteria decisions, road routing recommendation, intelligent control of energy consumption, fuzzy cognitive maps, and smart health. However, traditional fuzzy systems, neural network design, performance optimisation approaches, and application schemes are no longer sufficient and cannot satisfy and serve future smart cities effectively with regards to complex operations, intelligent multi-objective optimisation and advanced diversity form applications. There is therefore a need for a novel paradigm of reliable computational and neural models and optimisation programs to solve the challenges faced in smart cities.

The aim of this Special Issue is to pursue first-class research along this direction by promoting the scaling-up of design, optimisation, and applications of AIFS for smart cities, the development of fuzzy based smart city models, the fuzzy optimisation of wireless charging systems, the extension to self-supervised, multi-intelligent, and robust dynamic programming. We also welcome work relating to unmanned aerial vehicle (UAV)-based smart applications, smart city social networks, big data cognitive computing, security and privacy protection of smart cities, intelligent medical treatment, emergency care, and multidimensional modelling of urban environments. We invite researchers and experts worldwide to submit high-quality innovative research papers and critical review articles on the subsequent potential topics.

Potential topics include but are not limited to the following:

  • Advanced AI-based algorithms for smart cities
  • Genetic/Swarm advanced intelligence algorithms in intelligent fuzzy systems for smart cities
  • Diversity applications with intelligent fuzzy computing in smart cities
  • Multi-intelligent and robust smart city fuzzy systems
  • Advanced intelligent fuzzy system design and networking optimisation for smart cities
  • Fuzzy based advanced intelligent charging scheduling optimisation for smart cities
  • Incentives for smart city video surveillance systems
  • Advanced intelligent wireless charging systems for electric vehicle networks
  • Deployment and management for smart cities with advanced intelligent fuzzy systems
  • Advanced intelligence optimisation algorithms in fuzzy systems
  • Advanced intelligent big data analytics in smart city-based fuzzy systems
  • Security and privacy protection of smart cities
  • Fuzzy based location privacy techniques deployed in electric vehicle networks
  • Decision support systems for smart cities using advanced intelligent fuzzy systems

Articles

  • Special Issue
  • - Volume 2020
  • - Article ID 4864128
  • - Research Article

Rank Estimation for Mean Residual Life Transformation Model

Xiaoping Chen
  • Special Issue
  • - Volume 2020
  • - Article ID 6673535
  • - Research Article

A Novel Consumer Purchase Behavior Recognition Method Using Ensemble Learning Algorithm

Peng Wang | Zhengliang Xu
  • Special Issue
  • - Volume 2020
  • - Article ID 6692257
  • - Research Article

Crowd Counting and Abnormal Behavior Detection via Multiscale GAN Network Combined with Deep Optical Flow

Beibei Song | Rui Sheng
  • Special Issue
  • - Volume 2020
  • - Article ID 6615252
  • - Research Article

Signal Reconstruction Based on Probabilistic Dictionary Learning Combined with Group Sparse Representation Clustering

Bin Liang | Shuxing Liu
  • Special Issue
  • - Volume 2020
  • - Article ID 8842784
  • - Research Article

An Indoor Positioning Algorithm for Wearable Device Using Deep Learning Regression Prediction Model in IoT Applications

Aichuan Li | Shujuan Yi
  • Special Issue
  • - Volume 2020
  • - Article ID 6613896
  • - Research Article

Dynamic Knowledge Inference Based on Bayesian Network Learning

Deyan Wang | Adam AmrilJaharadak | Ying Xiao
  • Special Issue
  • - Volume 2020
  • - Article ID 6625695
  • - Research Article

A Novel Detection Framework for Detecting Abnormal Human Behavior

Chengfei Wu | Zixuan Cheng
  • Special Issue
  • - Volume 2020
  • - Article ID 8874057
  • - Research Article

[Retracted] Safety Investment Decision Problem without Probability Distribution: A Robust Optimization Approach

Chunlin Xin | Jianwen Zhang | ... | Sang-Bing Tsai
  • Special Issue
  • - Volume 2020
  • - Article ID 6343705
  • - Research Article

A Data Mining Method Using Deep Learning for Anomaly Detection in Cloud Computing Environment

Jin Gao | Jiaquan Liu | ... | Xinyang Wang
  • Special Issue
  • - Volume 2020
  • - Article ID 8884227
  • - Research Article

[Retracted] An Empirical Study on Customer Segmentation by Purchase Behaviors Using a RFM Model and K-Means Algorithm

Jun Wu | Li Shi | ... | Guangshu Xu
Mathematical Problems in Engineering
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Acceptance rate11%
Submission to final decision118 days
Acceptance to publication28 days
CiteScore2.600
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