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Nonlinear network disturbance suppression based on chaos optimization algorithm

INTERNATIONAL JOURNAL OF SYSTEM ASSURANCE ENGINEERING AND MANAGEMENT 2023年第1期14卷 110-119页

作者： Zhang, Zefeng Chen, Kan Xinyang Vocat & Tech Coll Xinyang 464000 Peoples R China

Because the existing methods do not consider the random data packet loss problem, there is a large test error, and the problem of non-static disturbance suppression cannot be achieved. For this reason, a nonlinear network disturbance suppression method based on chaos optimization algorithm is proposed. Given the basic structure of the nonlinear network control system, it is concluded that the nonlinear network is mainly affected by uplink interference and downlink interference. A class of nonlinear network control systems with random packet loss data is studied. The protection entropy is obtained to monitor the packet loss data. Finally, a chaos optimization algorithm is used to suppress nonlinear network disturbances. The experimental results show that the proposed method can effectively suppress the disturbance under the uplink interference and downlink interference, and the test error is relatively small, the mean square error is 0.29, the maximum positive error is 0.521, and the maximum negative error is 0.21, which shows that the method is effective and can eliminate the influence of interference factors on the stability of nonlinear network.

关键词： chaos optimization algorithm Nonlinear network Disturbance suppression Packet loss data Protection entropy

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Numerical Simulation of a Multi-Output Radar Orthogonal Waveform Based on a chaos optimization algorithm

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RUSSIAN PHYSICS JOURNAL 2022年第9期64卷 1599-1612页

作者： Sun, Caifeng Lopez, Miguel A. Shanxi Datong Univ Coll Phys & Elect Sci Datong Peoples R China Univ Castilla La Mancha Polytech Sch Cuenca Dept Math Cuenca Spain Univ Castilla La Mancha Inst Appl Math Sci & Engn IMACI Cuenca Spain

Aiming at problems of low probability of interception and poor anti-jamming performance of the multi-output radar, the numerical simulation based on a chaos optimization algorithm is proposed. Firstly, chaotic frequency coding is applied to the multi-output radar signal, and different frequency modulation methods are applied to different subpulses. At the same time, in view of the low efficiency of the numerical simulation algorithm in large space and high dimensional optimization, the GASA algorithm is used to increase the diversity of chaotic optimization algorithm search process. According to the specific working mode, the initial phase of each cycle of the multi-output radar orthogonal waveform is obtained, and the number of numerical simulations of multi-output radar orthogonal waveforms is established by the Model. Experimental results show that the proposed method can improve the radar energy utilization and signal-to-noise ratio, allocate reasonably the transmitting energy, and keep the structural stability of the LFM signal frequency changing continuously with time.

关键词： numerical simulation chaos optimization algorithm MIMO radar

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Scheduling of manufacturers based on chaos optimization algorithm in cloud manufacturing

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ROBOTICS AND COMPUTER-INTEGRATED MANUFACTURING 2019年 58卷 13-20页

作者： Hu, Yanjuan Zhu, Feifan Zhang, Lin Lui, Yongkui Wang, Zhanli Changchun Univ Technol Sch Mechatron Engn Changchun 130012 Jilin Peoples R China Beihang Univ Sch Automat Sci & Elect Engn Beijing 100191 Peoples R China Xidian Univ Sch Mechanoelect Engn Ctr Smart Mfg Syst Xian 710071 Shaanxi Peoples R China

With the rapid development of cloud manufacturing (CMfg) technology in Industrial Internet based on the concept of manufacturing as a service, how to effectively and quickly implement manufacturer scheduling in a cloud manufacturing environment has aroused widespread attention of researchers. Manufacturers in the cloud manufacturing environment are virtualized and digitized, and then aggregated in the form of cloud data. As a direct provider of cloud manufacturing services, manufacturers shift the service mode from the traditional de central type to a centralized type. However, in practice, manufacturers can't respond promptly to the needs of customer. The scheduling of manufacturers will directly affect the quality of cloud manufacturing services. This paper research the problem of manufacturer scheduling in the cloud manufacturing environment and analyzes the factors that affect the manufacturer resource scheduling in five categories including task load degree, task reliability, manufacturing efficiency, manufacturing resource richness and Internet of Things (IoT) match degree. At the same time, we establishes the scheduling index and the objective function model. The chaos optimization algorithm (COA) is used to solve the objective function and achieve scheduling of manufacturers under different scheduling tasks. The simulation results show that the proposed scheduling index is comprehensive and effective. Based on the math model of manufacturer scheduling, all the factors that influence the manufacturer scheduling in the cloud manufacturing environment can be merged together, and the complicated scheduling problem also can be transformed into the mathematical problem to solve. In this paper, the manufacturer scheduling algorithm based on chaos Theory can finish the scheduling of manufacturers under various tasks and make the cloud manufacturing platform provide manufacturing services to users in time.

关键词： Cloud manufacturing Manufacturer Scheduling chaos optimization algorithm AHP

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A New Method in RFID Anti-Collision Protocol using chaos optimization algorithm 27

A New Method in RFID Anti-Collision Protocol using Chaos Opt...

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27th Iranian Conference on Electrical Engineering (ICEE)

作者： Siri, Elham Golsorkhtabaramiri, Mehdi Safaei, Amir Islamic Azad Univ Babol Branch Dept Comp Engn Babol Sar Iran Univ Zanjan Dept Elect Engn Zanjan Iran

ISBN: (纸本)9781728115085

One of the main challenges in modern anti-collision algorithms in RFID systems is to estimate the number of collided tags in each slot of identification process. This paper presents a novel solution in Vogt tag estimation algorithm which is used in assigned tree slotted aloha (ATSA) method based on chaos optimization algorithm. This method has been examined with logistic chaotic map and outcomes are compared with classical method. Simulation is accomplished with 12-bit ID which covers the full serial number bit length and the tags number are considered up to 4096 tags. Some criterions such as the number of collision slots, idle slots, and total slots are compared and simulation results show an improvement in system throughput.

关键词： RFID assigned tree slotted Aloha Vogt algorithm anti-collision chaos optimization algorithm

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A New Method in RFID Anti-Collision Protocol using chaos optimization algorithm

A New Method in RFID Anti-Collision Protocol using Chaos Opt...

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Iranian Conference on Electrical Engineering

作者： Elham Siri Mehdi Golsorkhtabaramiri Amir Safaei Department of Computer Engineering Babol Branch Islamic Azad University Babol Iran Department of Electrical Engineering University of Zanjan Zanjan Iran

关键词： RFID Assigned tree slotted aloha Vogt algorithm Anti-collision chaos optimization algorithm

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Solving Robust Reliability Index Based on the Mutative Scale chaos optimization algorithm

Solving Robust Reliability Index Based on the Mutative Scale...

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2nd Global Conference on Civil, Structural and Environmental Engineering (GCCSEE 2013)

作者： Zhang Feng He Xindang Nan Hua Ren Hao Northwestern Polytech Univ Sch Mech Civil Engn & Architecture Xian 710129 Peoples R China

ISBN: (纸本)9783037859261

A novel method based on the mutative scale chaos optimization algorithm is proposed to solve the robust reliability index of non-probabilistic reliability model. Compared with the basic chaos optimization method, this novel method can minimize searching area of optimization variable and change the adjustable parameters of next search stage for improving the optimization performance. The proposed optimization algorithm is more efficient and has smaller computational complexity in solving robust reliability index. The feasibility and efficiency of the proposed method are demonstrated by two examples.

关键词： non-probabilistic reliability model robust reliability index mutative scale chaos optimization algorithm

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An improved particle swarm optimization combined with double-chaos search

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MATHEMATICAL BIOSCIENCES AND ENGINEERING 2023年第9期20卷 15737-15764页

作者： Zheng, Xuepeng Nie, Bin Chen, Jiandong Du, Yuwen Zhang, Yuchao Jin, Haike Jiangxi Univ Chinese Med Sch Comp Nanchang 330004 Peoples R China

Particle swarm optimization (PSO) has been successfully applied to various complex optimization problems due to its simplicity and efficiency. However, the update strategy of the standard PSO algorithm is to learn from the global best particle, making it difficult to maintain diversity in the population and prone to premature convergence due to being trapped in local optima. chaos search mechanism is an optimization technique based on chaotic dynamics, which utilizes the randomness and nonlinearity of a chaotic system for global search and can escape from local optima. To overcome the limitations of PSO, an improved particle swarm optimization combined with double-chaos search (DCS-PSO) is proposed in this paper. In DCS-PSO, we first introduce double-chaos search mechanism to narrow the search space, which enables PSO to focus on the neighborhood of the optimal solution and reduces the probability that the swarm gets trapped into a local optimum. Second, to enhance the population diversity, the logistic map is employed to perform a global search in the narrowed search space and the best solution found by both the logistic and population search guides the population to converge. Experimental results show that DCS-PSO can effectively narrow the search space and has better convergence accuracy and speed in most cases.

关键词： chaos optimization algorithm particle swarm optimization chaotic dynamics optimization problem

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An inspired chaos-based estimation-theory optimization for low-density parity-check (LDPC) code decoding

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RESULTS IN ENGINEERING 2024年 22卷

作者： Dahan, Fadl Roberts, Michaelraj Kingston Nagabushanam, Munivenkatappa Alfakih, Taha M. Prince Sattam bin Abdulaziz Univ Coll Business Adm Hawtat Bani Tamim Dept Management Informat Syst Al Kharj 11942 Saudi Arabia Sri Eshwar Coll Engn Ctr Adv Signal Proc & Sensor Networks Dept Elect & Commun Engn Coimbatore 641202 Tamil Nadu India MS Ramaiah Inst Technol Dept Elect & Commun Engn Bangalore Karnataka India Aljanad Univ Sci & Technol Fac Engn & Informat Technol Taizi Yemen

optimization techniques have emerged as powerful tools for solving complex engineering problems in real-time applications, surpassing traditional heuristic methods. This paper introduces a novel chaos optimization algorithm that integrates the bisection search method to enhance the convergence ability, solution accuracy, and search speed of conventional optimization problems. The proposed algorithm is applied to the design and analysis of a reduced complexity decoding scheme using Low-Density Parity-Check (LDPC) codes. By leveraging the Linear Minimum Mean Square Error (LMMSE) estimation criterion, the proposed method approximates the estimated parameters acquired during the message computation process. This combined approach effectively mitigates error propagation and premature convergence issues. The presented research offers a low-complexity decoding algorithm for LDPC codes, leveraging an optimized chaos bisection search method. The adoption of the LMMSE criterion overcomes data dependency and error propagation concerns during the estimation process. The modified chaos optimization technique, integrated with the bisection search, efficiently determines optimal values from perturbed observations, leading to improved convergence rates and data processing precision by reducing the observation dimension (search space). Simulation results validate the proposed approach, showcasing its ability to mitigate error propagation and premature convergence while maintaining coding gain accuracy. Experimental validation on an FPGA RF-SoC device (model XCZU27DR) demonstrates that the proposed method achieves a maximum throughput of 8.7 Gbps at a clock frequency of 386.72 MHz, with reduced hardware complexity. The experimental verification on an FPGA RF-SoC device highlights the algorithm's minimal hardware complexity, superior decoding throughput, and Bit Error Rate (BER) performance.

关键词： chaos optimization algorithm Bisection search method Linear minimum mean square estimation (LMMSE) FPGA design LDPC codes Sustainable development goals (SDGs)

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Defining the Settings of Product Attributes for Product Design Using an Innovative NSGA-II

Defining the Settings of Product Attributes for Product Desi...

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International Conference on Frontiers of Artificial Intelligence and Machine Learning (FAIML)

作者： Jiang, Huimin Sabetzadeh, Farzad Macau Univ Sci & Technol Sch Business Taipa Macao Peoples R China City Univ Macau Fac Business Taipa Macao Peoples R China

ISBN: (数字)9781665473644

ISBN: (纸本)9781665473644

In the process of product design, the quality function deployment and affective design are needed in the initial stage. In fact, for a new product, affective design needs designers, and engineering design needs engineers to complete. Generally, some design attributes in affective design and engineering specifications in engineering design are common. However, the two processes, quality function deployment and affective design, are carried out separately, so there will be some differences in the settings of the same design attributes and engineering specifications. This paper formulates a multi-objective optimization model which considers the above two processes. In order to optimize the design, an innovative non-dominated sorting genetic algorithm-II (NSGA-II) based on chaos optimization algorithm (COA) is proposed. At the same time, using the way of case analysis, the mobile phone is selected as the research object to illustrate the establishment of the model and the optimization technique.

关键词： new product design nsga-ii chaos optimization algorithm

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Interval partition relaxed sorting conjugate gradient chaos optimization algorithm

Interval partition relaxed sorting conjugate gradient chaos ...

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32nd Chinese Control Conference (CCC)

作者： Li Xiao-sheng Zhang Guo-shan Wang Jian-kui Tianjin Univ Sch Elect Engn & Automat Tianjin 300072 Peoples R China

ISBN: (纸本)9781479900305

This paper presents an interval partition relaxed sorting conjugate gradient chaos optimization algorithm (IPRSCGCOA). The new algorithm adopts the interval partition chaos search and relaxed sorting to locate search points near the global optimal solution. The conjugate gradient algorithm is further used to achieve the global optimal solution. The simulation of the new algorithm and the other method shows that the new algorithm is effective to reach the global optimal solution with better stability, better convergence precision and less iteration number. Moreover, the effectiveness of the relaxed sorting is analyzed, the relationship between interval partition number and the effectiveness of the algorithm is discussed, and the optimal interval partition numbers of the simulation examples are given.

关键词： chaos optimization algorithm Interval Partition Relaxed Sorting Conjugate Gradient Method

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