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2nd International Conference on Mechatronics and Intelligent Materials (MIM 2012)

作者： Wang, Da Bian, Hongyu Harbin Engn Univ Coll Underwater Acoust Engn Harbin 150001 Peoples R China

ISBN: (纸本)9783037853849

In order to further improve the accuracy of the sonar image registration, a novel hybrid algorithm was proposed. It proposed the normalized mutual information as similar estimation, drawn on multi-resolution data structure based on wavelet transform, a low precision solution was solved by improved pso algorithm, which has strong global search capability, firstly and then a high precision solution was acquired by Powell method, which has strong local search capability. The hybrid algorithm is effective to overcome the fall of local maximum mutual information function;it also improves solution's precision. Since the hybrid algorithm is the initial point of pre-treatment, an effective solution to the Powell method dependence on the initial point. Experiments reveal that the hybrid algorithm is efficiency and effectiveness.

关键词： Image Registration pso algorithm Powell algorithm Mutual Information Sonar Images

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A High-Efficiency Codesign Method for Bandgap Circuit by Submodule Optimization

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INTERNATIONAL JOURNAL OF CIRCUIT THEORY AND APPLICATIONS 2025年第0期

作者： Yang, Yunqi Chen, Dongdong Wang, Xianglong Li, Di Yang, Yintang Xidian Univ Fac Integrated Circuit Xian Peoples R China

In this paper, a high-efficiency codesign method for bandgap circuit (BGR) circuit by submodule optimization is proposed. In the proposed method, the BGR circuit is divided into operation amplifier module (OPM) and reference voltage generation module (RVGM) to be separately optimized to improve the optimization design efficiency. Firstly, the OPM is optimized based on neural network (NN) model and particle swarm optimization (pso) algorithm. NN models are established to describe the relationship between design parameters and performance metrics of OPM, and then the parameters of OPM are optimized by pso algorithm according to the established optimization function with constraints. The parameters of RVGM are optimized based on the optimized OPM. The high-accuracy approximate equations of temperature coefficient (TC) are established based on compensation functions. The TC, total area, and total power consumption are co-optimized by interior point method. According to the optimized parameters of OPM and RVGM, the verifications are conducted by Cadence. The results show that the proposed method can greatly improve the design efficiency of BGR circuit, whose total running time is only 552.5 s. Meanwhile, the optimized TC is 4.76 ppm/degrees C over -40 degrees C-125 degrees C at 2.5-V supply, and the optimized area and power consumption are 0.0187 mm2 and 288.5 mu W. The Monte Carlo results show that Vref has a standard deviation of 1.503 mV, which is only 0.12% across 1000 runs, so the Vref is very stable. Therefore, the proposed codesign method can be used to effectively optimize the BGR circuit.

关键词： bandgap reference circuit codesign optimization method NN model pso algorithm

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An Efficient Dynamic Priority-Queue algorithm Based on AHP and pso for Task Scheduling in Cloud Computing 1

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16th International Conference on Hybrid Intelligent Systems (HIS) / 8th World Congress on Nature and Biologically Inspired Computing (NaBIC)

作者： Ben Alla, Hicham Ben Alla, Said Ezzati, Abdellah Touhafi, Abdellah Hassan 1 Univ LAVETE Lab Sci & Tech Fac Sci & Tech FacMath & Comp Sci Dept Settat 26000 Morocco Vrije Univ Brussel Dept Elect & Informat ETRO Pl Laan 2 B-1050 Brussels Belgium

ISBN: (数字)9783319529417

ISBN: (纸本)9783319529417;9783319529400

Nowadays Cloud Computing is an emerging technology in the area of parallel and distributed computing. Task scheduling is one of the major issues in cloud computing, which plays an important role to improve the overall performance and services of the cloud. Task scheduling in cloud computing means assign best suitable resources for the task to be executed with the consideration of different parameters like execution time, user priority, cost, scalability, throughput, makespan, resource utilization and so on. In this paper, we address the challenge of task scheduling, and we consider one of most critical issues in scheduling process such as the task priorities. The goal of this paper is to propose an efficient Dynamic Priority-Queue (DPQ) algorithm based on Analytic Hierarchy Process (AHP) with Particle Swarm Optimization (pso) algorithm. The proposed algorithm DPQ-pso gives full consideration to the dynamic characteristics of the cloud computing environment. Further, the proposed algorithm has been validated through the CloudSim simulator. The experimental results validate that the proposed approach can effectively achieve good performance, user priority, load balancing, and improve the resource utilization.

关键词： Cloud computing pso algorithm AHP DPQ-pso algorithm Task scheduling Dynamic queues

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Research on Random Collision Detection algorithm Based on Improved pso

Research on Random Collision Detection Algorithm Based on Im...

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2nd International Conference on Information Computing and Applications

作者： Hu, Ting-dong Shenzhen Kunyiziyuan Elect Ltd Shenzhen Peoples R China

ISBN: (纸本)9783642252549

In order to improve the real-time of collision detection algorithm, this paper introduces particle swarm optimization (pso), pso simple and easy to operate, and search capability and convergence speed have a greater advantage. To reduce the random collision detection algorithm missed some of the interfering elements and to improve the accuracy of collision detection, using the OBB bounding box surrounding the basic geometric elements instead of the basic geometric elements characterized as a random sampling point collision detection method. The complex three-dimensional models of the collision problem are transformed into simple two-dimensional discrete space optimization problems, and improve the algorithm in real time.

关键词： Random collision detection pso algorithm OBB particles collision detection

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Lithium-ion batteries state of charge estimation using pso-BP neural network improved UKF algorithm 39

Lithium-ion batteries state of charge estimation using PSO-B...

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39th Youth Academic Annual Conference of Chinese-Association-of-Automation (YAC)

作者： Pu, Long Wang, Chun Chen, Junlin Sichuan Univ Sci & Engn Sch Mech Engn Zigong Peoples R China

ISBN: (纸本)9798350390780;9798350379228

To tackle the issue of inaccurate state of charge (SOC) estimation in lithium-ion batteries when employing the unscented Kalman filter (UKF) in real-world applications, a refined approach utilizing the pso-BP neural network is introduced to enhance the performance of UKF for SOC estimation. Firstly, the Thevenin model is identified using particle swarm optimization (pso). Secondly, the pso-BP is trained by using the characteristic parameters related to the estimation error of UKF. Finally, the UKF SOC estimate error was corrected using the trained pso-BP. Experimental results demonstrate that the proposed algorithm significantly enhances SOC estimation accuracy.

关键词： SOC estimation pso algorithm BP UKF

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Multi-Objective Design Optimization of PMSM for PEM Fuel Cell Air-Circuit with pso algorithms

Multi-Objective Design Optimization of PMSM for PEM Fuel Cel...

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IEEE International Electric Machines and Drives Conference (IEMDC 2009)

作者： Sari, Ali Dubas, Frederic Espanet, Christophe Univ Franche Comte FEMTO ST Inst UMR 6174 CNRS F-90010 Belfort France

ISBN: (纸本)9781424442515

This paper deals with the design of a 500 W permanent magnet (PM) synchronous motor (PMSM) used to drive the air-compressor of a 5 kW fuel cell (FC). The authors focus on the optimization of the PMSM efficiency/mass/efficiency-mass in order to minimize the energy consumption and the mass of the air-compressor which can represent up to 30 % of the electrical energy delivered by the FC. The aim of this paper is the optimization of the PMSM for proton exchange membrane (PEM) FC air-circuit with an analytical model (AM) based on the Maxwell's equations and with the particle swarm optimization (pso) algorithm. The results are compared to finite element analysis (IFEA) and make it possible to define the characteristics that have the highest influence on the PMSM performances.

关键词： Fuel cell ancillaries compressor analytical model optimization pso algorithm permanent magnet machine

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Efficient and adaptive design of RBF neural network for maximum energy harvesting from standalone PV system

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SUSTAINABLE COMPUTING-INFORMATICS & SYSTEMS 2025年 46卷

作者： Kacimi, Mohand Akli Aoughlis, Celia Bakir, Toufik Guenounou, Ouahib Univ Bejaia Fac Technol Lab Technol Industrielle & Informat LTII Bejaia 06000 Algeria Univ Burgundy French Comte Lab Image & Artificial Vis ImViA Dijon France

This paper deals with a topical topic, the maximum energy harvest of standalone PV system under varying conditions. It introduces a new approach based on the use of artificial intelligence and machine learning to overcome the usual weaknesses of conventional Maximum Power Point Tracking (MPPT) techniques and to improve solutions to meet growing energy demand and further promote sustainable development. The proposal consists of using Radial Basis Function Neural Network (RBFNN) tuned by a pso algorithm as MPPT controller. The main aim of this combination (RBFNN-pso) is to achieve the best compromise between the control accuracy and complexity, while using a simple optimization algorithm. This aim is motivated by the potential of the neural networks to learn from any tasks and to generalize the acquired knowledge to other situation never seen before. The proposal reaches a high efficiency and high energy harvesting with a yield greater than 99 %. The performed comparative study with other intelligent techniques from literature prove the superiority and the promising potential of the introduced approach. The developed work presented in this paper is developed with MatLab/ Simulink environment.

关键词： Automatic learning Accuracy-complexity trade-off MPPT control Optimization pso algorithm RBF neural network Smart grid

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Comparative Study on Several pso algorithms

Comparative Study on Several PSO Algorithms

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26th Chinese Control and Decision Conference (CCDC)

作者： Jiang, Weichang Zhang, Yating Wang, Ruihua Beijing Univ Technol Elect Informat & Control Engn Coll Beijing 100124 Peoples R China

ISBN: (纸本)9781479937066

With the development of intelligent algorithm, GA and pso have become the hot spot for the study on multi-objective optimization in recently years. Information sharing is the core of pso algorithm, Comparing with GA, pso algorithm has less variables to adjust and is easy to achieve, so it is widely used in engineering. This paper focus on the comparation on several pso algorithm and introduce a kind of pso algorithm that is better in performance than others

关键词： pso algorithm Intelligent algorithm Selpso

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Combing Fuzzy Clustering and pso algorithms to Optimize Energy Consumption in WSN Networks 4

Combing Fuzzy Clustering and PSO Algorithms to Optimize Ener...

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IEEE SmartWorld, Ubiquitous Intelligence & Computing, Advanced & Trusted Computing, Scalable Computing & Communications, Cloud & Big Data Computing, Internet of People and Smart City Innovation (SmartWorld/SCALCOM/UIC/ATC/CBDCom/IOP/SCI)

作者： Javadpour, Amir Adelpour, Niusha Wang, Guojun Peng, Tao Guangzhou Univ Sch Comp Sci & Technol Guangzhou 510006 Guangdong Peoples R China Islamic Azad Univ Dept Comp Sci & Technol Tehran *** Iran

ISBN: (纸本)9781538693803

In wireless sensor networks, nodes are distributed in the environment and there is no access to replace batteries. Therefore, providing an algorithm to reduce energy consumption is a great major challenge. Heuristic algorithms can find best solutions (close to optimal solution) in a short time for nondeterministic polynomial problems. Thus, these algorithms are applied in optimal problems in math and artificial intelligence because math optimization methods are slow to find optimal solution or cannot find solution. In this paper, Fuzzy clustering is used to join sensors in the network and the particle swarm optimization algorithm (pso) is used to estimate the initial value of cluster heads. Then, we evaluate our proposed method by NS2 simulator. The proposed algorithm is compared with Enhanced optimized energy efficient routing protocol E-OEEPR which is investigated by energy consumption, Packet Delivery Ratio (PDR) and network throughput.

关键词： E-OEEPR artificial intelligence energy consumption Fuzzy clustering pso algorithm wireless sensor networks

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Experimental and numerical investigation on ductile fracture behavior of welded areas under tensile and shear forces

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ENGINEERING STRUCTURES 2025年 329卷

作者： Wang, Yifei Tong, Lewei Shi, Weizhou Tongji Univ Coll Civil Engn Shanghai 200092 Peoples R China Shanghai Inst Architectural Design & Res Co Ltd Shanghai 200041 Peoples R China Shanghai Engn Res Ctr Assembly Bldg Technol Integr Shanghai 200011 Peoples R China

Due to complex stress conditions, welded joints in steel and concrete-filled steel tubular trusses are considered weak parts and are susceptible to failure by fracture. To investigate the ductile fracture behavior of steel tubular welded joints under a combination of tension and shear, this study took 36 specimens from the base/tube metal (BM), heat-affected zone (HAZ) and weld metal (WM) in welded areas. The fracture behavior of five kinds of specimens were compared. Then, to simulate fracture patterns of specimens, this study developed a new Shear- Modified GTN model (SMGTN), which was based on two types of damage variables: tension and shear. The particle swarm optimization (pso) algorithm was employed to calibrate SMGTN model parameters. Finally, the stress conditions, damage, and fracture patterns of various specimens were analyzed. The result demonstrated that the larger the radius or shear center rotation angle of notched specimens, the larger the fracture displacement. The materials in BM, HAZ, and WM regions exhibited different ductile behavior under different stress conditions. The calibrated parameters of SMGTN model in this study accurately predicted the fracture displacement and development patterns in the BM, HAZ, and WM regions.

关键词： Q355 BM-HZA-WM Tension Shear And combined stress conditions Shear-modified GTN model pso algorithm Damage evolution and fracture prediction

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