Swarm Optimization Algorithm IEEE PAPERS AND PROJECTS-2020



Particle swarm optimization (PSO) algorithm is a stochastic optimization technique based on swarm, which was proposed by Eberhart and Kennedy (1995) and Kennedy and Eberhart (1995). PSO algorithm simulates animal’s social behavior, including insects, herds, birds and fishes
The most common term for methods that employ stochastic schemes to produce search strategies is metaheuristics. In general, there not exist strict classifications of these methods. However, several kinds of algorithms have been coined depending on several criteria such



Hybrid quantum particle swarm optimization algorithm and its application
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Dear editor, Quantum-behaved particle swarm optimization (QPSO) is an evolutionary algorithm with quantum behavior. It can be used to solve optimization problems by establishing a potential well at the local attraction point to influence the location of particles The present study suggests an integrated approach for determining the optimal release policy for the Mula reservoir situated at the Godavari basin, India. The proposed integrated algorithm named DP-PSO is a hybridization of Dynamic Programming (DP) and Particle The classification accuracy of a multi-layer perceptron (MLP) depends on the selection of relevant features from the data set, its architecture, connection weights and the transfer functions. Generating an optimal value of all these parameters together is a complex task In this paper, we propose an efficient discrete wavelet transform-based compression method for color images. Generally, the strong correlation exists between the three planes R, G, and B of a color image, where the decrease of this correlation gives an improvement in the In this study, an analytical prediction model was utilized to predict the residual stresses induced during pre-stressed cutting of thin-walled ring, and the results were validated by experiments. General multivariate regression predictive models were presented to Clustering is an unsupervised technique that groups the similar data objects into a single subset using a distance function. It is also used to find the optimal set of clusters in a given dataset and each cluster consists of homogenous data objects. In present work, an algorithm Image segmentation has considered an important step in image processing. Fuzzy c-means (FCM) is one of the commonly used clustering algorithms because of its simplicity and effectiveness. However, FCM has the disadvantages of sensitivity to initial values, falling Protein protein interaction plays an important role in biological function. Though protein interaction and non-interaction is a broad field, PPI is considered more important than PPNI. The concentration of dataset with PPNI is also used to predict the protein protein interaction In medical field, securing every patients record is main concern, ascribed to many fraudulent cases occurring in the health sector. The data of every individual must be engraved and sent into end-user without any issues. Mainly in the healthcare industry, where thoughts are oftenDue to the growing demand for electrical power, the researchers are trying to fulfill this demand by considering different ways of renewable energy resource as existing energy resources failed to do so. The solar energy from the sun is freely available, and by using Aiming at vehicle routing problem and combining the advantages of ant colony and particle swarm optimization, an intelligent optimization algorithm of adaptive ant colony and particle swarm optimization is proposed. Through the simulation of ant colony and bird swarm

Particle Swarm Optimization for Performance Management in Multi-cluster IoT Edge Architectures.
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By designing a controller and using a particle swarm optimization algorithm we can demonstrate that processing and propagation delay and the end-to-end latency (ie, total response time) can be optimized. 1 INTRODUCTION

A fractional PID controller based on particle swarm optimization algorithm
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Fractional PID controller is a convenient fractional structure that has been used to solve many problems in automatic control. The fractional scale proportional-integral-differential controller is a generalization of the integer order PID controller in the complex domain. By

Optimization of Intermittent Water Supply Systems Using Particle Swarm Optimization Algorithm and Pressure Driven Hydraulic Analysis
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In this research, intermittent water supply is optimized using pressure driven hydraulic analysis and particle swarm optimization algorithm with the aim of maximizing the uniformity of water distribution in the network and reliability. In the following, by calculating the

An Improved Particle Swarm Optimization Algorithm Based on Restart Strategy
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In order to solving the problems of premature convergence and local extremum caused by traditional particle swarm optimization algorithm (PSO algorithm), this paper proposes an improved particle swarm optimization algorithm based on restart strategy (BRSPSO

A Standardized Bare Bones Particle Swarm Optimization Algorithm for Traveling Salesman Problem
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The traveling salesman problem (TSP) plays an important role in theoretical computer science. It can be used to solve different route planning problems in the real world and has been proved to be NP-hard. Plenty of researchers tried to solve the TSP by the population Among them, the competitive swarm optimizer is a new optimization algorithm proposed in recent years, which is based on particle swarm optimization algorithm and has achieved good results in high-dimensional feature selection problems, but it also has the problems of high In the literature, several variants of cat swarm optimization (CSO) algorithm are reported. However, CSO for integer multiobjective optimization problems (MOPs) has not yet been investigated. Owing to the frequent occurrence of integer MOPs and their importance in

A two-sink based Particle Swarm Optimization Algorithm for Wireless Body Area Networks.
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Routing is one of the major challenges in designingwireless body area networks. Evolutionary-based Multihop Routing Protocol for wireless body area network is the first protocol offered for body surface networks. Some disadvantages of this protocol are as 1-ItTo address these issues, a new evolutionary technique called generalized space transformation search is proposed, and then, we introduce an improved quantum-behaved particle swarm optimization algorithm combined with this new technique in this study

Direct Torque Control Induction Motor Drive for Speed Estimation Using Modified Particle Swarm Optimization Algorithm
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In this study, the current and flux linkage of a stator were used to develop a speed estimation direct torque control induction motor (IM) drive, and the speed estimation signal was derived from the stator flux observer. Hall effect current sensors were used to obtain the stator

Darts Game Optimizer: A New Optimization Technique Based on Darts Game
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Page 1. Received: April 1 2020. Revised: July 2020. 286 International Journal of Intelligent Engineering and Systems, Vol.1 No. DOI: 10.22266/ijies2020.1031.26 Darts Game Optimizer: A New Optimization Technique Based on Darts GameTwitter is a Social Media that distributes opinions and sentiments of the people in day today life to friends and general public. Many people use twitter to communicate their side effects/benefits of diabetic medicines. Other people in turn seek these posts to gain feedback

Speed Estimation of Adaptive Stator-flux-vector-controlled Induction Motor Drive Based on Particle Swarm Optimization Algorithm
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An adaptive synchronous speed estimation scheme is proposed for the speed estimation of a stator-flux-vector-controlled (SFVC) induction motor (IM) drive. An SFVC IM drive was established according to the current and flux of the stator, and the stator current was

THE APPLICATION OF PARTICLE SWARM OPTIMIZATION ALGORITHM TO PLAN REDESIGNS OF RESIDENTIAL COMPLEXES. A CASE STUDY IN THE HIGH
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The special features of some old residential complexes make reconstructing a better option than rebuilding. The complexity of redesign issues, the ability of computers to solve problems, and the capability of evolutionary optimization techniques in architecture make

TWO STRATEGY COOPERATIVE PARTICLE SWARM OPTIMIZATION ALGORITHM WITH INDEPENDENT PARAMETER ADJUSTMENT AND ITS
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Aiming at the premature convergence of particle swarm optimization (PSO) in solving complex multimodal problems, a two strategy cooperative particle swarm optimization algorithm (TSPSO) with independent parameter adjustment is proposed. In the proposed

Research on Particle Swarm Optimization Algorithm Based on Quantum Computing Technology
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G Wang American Journal of Electrical and article In view of the shortcomings of particle swarm optimization such as premature convergence to local optimization, particle swarm optimization algorithm based on quantum gate and particle swarm optimization algorithm based on quantum behavior are studied in this paper

PATTERNS IN PARKINSON CONDITION IN SUBTHALAMIC NUCLEUS MODEL OF BASAL GANGLIA USING PARTICLE SWARM OPTIMIZATION ALGORITHM
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Parkinson disease is a well-known movement disorder in which production of dopamine in the brain reduces. In this paper, we have considered a conductance-based model of subthalamic nucleus and globus pallidus (external) for a primate suffering from Parkinsonrandom numbers in the range of (0,1). 2.3 Bio-inspired computing In this paper, a particle swarm optimization algorithm based on chaos theory is pre- sented. Chaos represents a widespread nonlinear dynamic phenomenon [9

Efficient Integer Categorical Particle Swarm Optimization Algorithm and Cloud IoT for Health Service
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Cloud computing for HCS can restore patients records, diseases diagnosis and monitoring patient from wearable device as medical body area network other medical domains in less time and less of cost execution time. In cloud computing using cloud broker that proveid

A Classification Model using improved Hybrid Genetic Particle Swarm Optimization Algorithm based on Separability-Correlation Measure
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The unpredictable growth in information and data samples has engendered a crucial requirement for novel methodologies and mechanisms which can intellectually and spontaneously transform the processed information into valuable data and knowledge

A Hybrid Chicken Swarm Optimization with Tabu Search Algorithm for Solving Capacitated Vehicle Routing Problem
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In this paper the capacitated vehicle routing problem solved by Chicken Swarm Optimization algorithm Tabu Search and a new hybrid algorithm DOI: 10.22266/ijies2020.0831.21 Figure. 5 Chicken swarm optimization algorithm for solving CVRP

Particle Swarm Optimization Algorithm Combined with Genetic Algorithm, Gravitational Search Algorithm and Dynamic Cauchy Mutation for Power Loss
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Abstract; In this work particle swarm optimization (PSO) algorithm has been blended with Genetic algorithm (GA), Gravitational search algorithm (GSA), and intermingled with Dynamic Cauchy mutation to solve the reactive power problem. At first PSO merged with GA

Combinatorial Test Case Generation Method Based on Improved Particle Swarm Optimization Algorithm
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The combined test is difficult to achieve fully coverage about the all possibilities. In order to generate the least number of test cases, a method of test case set generation based on the combination of IPO strategy and CS-SPSO algorithm is proposed. Firstly, considering theAGO field is defined as follows: Artificial Birds are the basic entities in Particle Swarm Optimization algorithm The rest of the article is organized as follows: Particle Swarm Optimization algorithm is developed in Section 2. Section 3 presents God Particle Swarm Page 4

Novelty Swarm, the Implementation of Novelty Search in the Particle Swarm Optimization Algorithm
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The particle swarm optimization algorithm is based on swarm behaviour and has achieved important results in different applications. However, it is not exempt from stagnation in local optima and has a tendency to converge prematurely. Novelty Search is a concept that has

An Improved Hybrid Particle Swarm Optimization Algorithm to Minimize Total Flow Time and Makespan for no Wait Flow Shop Scheduling Problem
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Page 1. 1 Chapter 2 LITERATURE SURVEY 2.1 Introduction Production scheduling refers to the allocation of resources viz. labour, equipment, tools, etc. over time to accomplish specific tasks by fulfilling certain objective functions. The main objective behind theStability of swarms is considered in some works. In (Clerc and Kennedy 2002), the stability and convergence of particle swarm optimization algorithm is investigated. It analyzed the trajectory of particles in a discrete space and also in a continuous space

Optimal Sizing and Siting of Distributed Generators by Hybrid Particle Swarm Optimization-Grey Wolf Optimization Algorithm
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(Sci. Eng.) volume 73 (1), page no 129 13 2015. Manoela Kohler, Marley MBR Vellasco, Ricardo Tanscheit,PSO+: A new particle swarm optimization algorithm for constrained problems, Applied Soft Computing, Volume 8 December

Investigating the application of particle swarm optimization algorithm in the neural network to increase the accuracy of breast cancer prediction
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Introduction: Breast cancer usually begins from breast tissue and progresses rapidly. The disease is the most common cancer that women suffer from. With late diagnosis of breast cancer, the likelihood of the relapse of the disease is increased. The earlier breast cancer is

A Fast Quantum Particle Swarm Optimization Algorithm for Image Denoising Problem
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Noise can affect images while acquired, transmitted, stored or compressed. One of the best methods for noise removal is the sparse representation algorithm (SR). The Quantum Particle Swarm Optimization (QPSO) is one of the meta-heuristic algorithms. This paper

Grasshopper optimization algorithm for parameter estimation of photovoltaic modules based on the single diode model
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its modeling challenging. The accuracy and execution time obtained with GOA were compared with metaheuristic techniques such as genetic algorithm (GA) and particle swarm optimization algorithm (PSO). The analysis and maximizing network lifetime [ 10]. This work has anticipated an effectual Glowworm swarm optimization algorithm for improving energy effi- ciency and balancing load in a large scale WSN environ- ment. With the use of this Particle swarm optimization algorithm PSO is an evolutionary algorithm proposed by Kennedy and Eberhart in 1995 MSSE-PSO Jiang et al. Catfish effect particle swarm optimization algorithm CE-PSO Chuang et al. Constrained particle swarm optimization

Decreasing Weight Particle Swarm Optimization Combined with Unscented Particle Filter for the Non-Linear Model for Lithium Battery State of Charge
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Page 1. Int. J. Electrochem. Sci., 15 (2020) 10104 1011 doi: 10.20964/2020.10. 41 International Journal of ELECTROCHEMICAL SCIENCE www.electrochemsci. org Decreasing Weight Particle Swarm Optimization Combined

A Hybrid water cycle-particle swarm optimization for solving the fuzzy underground water confined steady flow
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Finally, all the rivers and/or streams end up in the sea, the most downhill (low-altitude) place in the world . Therefore, similar to a metaheuristic swarm optimization algorithm this phenomenon lends itself to finding a global optimal solution or a near-optimal solution via Existing methods converge to a local minimum. In this paper, a new multi-group particle swarm optimization algorithm (PSOEL) is proposed to solve the motion planning of manipulators. PSOEL consists of one elite group and several child groups

Distributed energy efficient backbone construction utilizing particle swarm optimization algorithm in wireless sensor networks with bidirectional links
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Connected dominating set (CDS) problem is the most widely used method for backbone formation in wireless sensor networks. To date, numerous algorithms have been proposed for backbone construction on minimum CDS (MCDS) problem in unit disk graphs (UDG); For example, the par- ticle swarm optimization algorithm simulates bird swarms foraging [45]; the fruit fly optimization algorithm simulates fruit fly feeding behavior [34]; the ant colony optimiza- tion algorithm takes inspiration from ant foraging [41]; and the gene algorithm mimics Page 1. Vol.:(0123456789) 1 3 Engineering with Computers 00997-x ORIGINAL ARTICLE A novel approach for forecasting of ground vibrations resulting from blasting: modified particle swarm optimization coupled extreme learning machineIn order to solve the above problems, this paper puts forward the adaptive manage- ment of virtual machine in cloud computing the particle swarm optimization algorithm in place and multi-objective optimization method based on multi-objective optimization model to construct

Modified salp swarm algorithm based multilevel thresholding for color image segmentation
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of threshold number. To avoid the above problem, the slap swarm optimization algorithm (SSA) is presented to choose the optimal parameters of the fitting function and we use levy flight to improve the SSA. The solutions are A New Viewpoint to Chaotic Particle Swarm Optimization via Gauss Map Hasan Koyuncu1

A Novel Gaussian Particle Swarms optimized Particle Filter Algorithm for the State of Charge Estimation of Lithium-ion Batteries
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This method also introduces normally distributed decay inertia weights to enhance the global search capability of the particle swarm optimization algorithm which improves the convergence of this estimation method 3.2. Gaussian particle swarm optimization algorithm theoryFurthermore, taking the minimum delay as the objective function and the number of fusion nodes and energy balance as the constraint, an aggregation node selection mecha- nism based on a swarm optimization algorithm is proposed to build a data aggregation tree based on

PARTICLE SWARM OPTIMIZATION BASED ON WEIGHTED AGGREGATION DEGREE AND ADAPTIVE DECISION
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In response to the problem that particle swarm optimization algorithm (PSO) is prone to falling into local optimum and premature convergence in later operations, this paper reconstructs the concept of weighted aggregation based on a redefined similarity to describe the degree

A novel hybrid antlion optimization algorithm for multi-objective task scheduling problems in cloud computing environments
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Page 1. A novel hybrid antlion optimization algorithm for multi-objective task scheduling problems in cloud computing environments Laith Abualigah1 Ali Diabat 3 Received: 24 December / Revised: 6 February

Solving Capacitated Vehicle Routing Problem Using Chicken Swarm Optimization with Genetic Algorithm
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the Capacitated Vehicle Routing Problem. This problem will be solved by hybrid algorithm combining Chicken Swarm Optimization algorithm with Genetic Algorithm using Crossover and Mutation operation. The main idea of In routing algorithm, route that have shortest path among multipaths selected by particle swarm optimization algorithm In routing algorithm, route that have shortest path among multipaths selected by particle swarm optimization algorithm