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13th International Power Electronics and Motion Control Conference

作者： Baghaee, H. R. Mirsalim, M. Sanjari, M. J. Gharehpetian, G. B. Amirkabir Univ Technol Ctr Excellence Power Engn Tehran Iran

ISBN: (纸本)9781424417414

In this paper, a new control strategy is proposed to limit the fault current in power systems which include distributed generation units. In the normal mode of operation, the series compensator sets as a line compensator. As soon as the fault is sensed, the new control mode is activated to limit the fault current, and properly interrupt the breaker. harmony search algorithm has also been used to optimize the parameters of series compensator controller. Simulations performed in MATLAB/Simulink environment indicate that the proposed control strategy performs well to limit the fault currents of distribution systems and restore the voltage at the point of common coupling to its preset value.

关键词： fault current limiter series compensator distributed generation harmony search algorithm

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Solving the shortest-path problem in logistics distribution for vehicle-routing optimization 12

Solving the shortest-path problem in logistics distribution ...

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12th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD)

作者： Jia, Baoxian Wang, Yong Yuan, Jinhai Li, Junqing Liaocheng Univ Coll Comp Sci Liaocheng 252059 Peoples R China Dongbei Univ Coll Comp Sci Shenyang 110006 Peoples R China

ISBN: (纸本)9781509040933

The classical harmony search (HS) algorithm has been improved. The algorithm effectively prevents it from becoming trapped by a local optimal solution. It allows to be used to deale the shortest-path issue. To solve the shortest route problem, we improved the classical harmony algorithm and seek the optimal solution in the global scope. Second, by the application of the dynamic priority value encoding scheme, we constructed the path based on the priority value of correspondent nodes of variables in the harmonic vector. Through the iterative update of the harmony memory banks, we finally obtained the shortest route. Finally the simulation experiments show us that the proposed algorithm is better than PSO algorithm and HS algorithm on the performance.

关键词： harmony search algorithm continuous optimization problems constrained optimization problems penalty function model shortest-path problem

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Detection of Black Hole Attacks in Mobile Ad Hoc Networks via HSA-CBDS Method

Detection of Black Hole Attacks in Mobile Ad Hoc Networks vi...

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1st International Conference on Intelligent Computing and Optimization (ICO)

作者： Fahad, Ahmed Mohammed Ahmed, Abdulghani Ali Alghushami, Abdullah H. Alani, Sammer Univ Malaysia Pahang Fac Comp Syst & Software Engn Kuantan 26300 Malaysia Community Coll Qatar Informat Technol Dept Doha Qatar UTEM Univ Fac Elect & Comp Engn FKEKK Durian Tunggal Malacca Malaysia

ISBN: (纸本)9783030009793;9783030009786

Security is a critical problem in implementing mobile ad hoc networks (MANETs) because of their vulnerability to routing attacks. Although providing authentication to packets at each stage can reduce the risk, routing attacks may still occur due to the delay in time of reporting and analyzing the packets. Therefore, this authentication process must be further investigated to develop efficient security techniques. This paper proposes a solution for detecting black hole attacks on MANET by using harmony search algorithm (DBHSA), which uses harmony search algorithm (HSA) to mitigate the lateness problem caused by cooperative bait detection scheme (CBDS). Data are simulated and analyzed using MATLAB. The simulation results of HSA, DSR, and CBDS-DSR are provided. This study also evaluates the manner through which HSA can reduce the inherent delay of CBDS. The proposed approach detects and prevents malicious nodes, such as black hole attacks that are launched in MANETs. The results further confirm that the HSA performs better than CBDS and DSR.

关键词： Dynamic source routing Cooperative bait detection scheme harmony search algorithm Black hole attack

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A hybrid GWO-PSO algorithm for Load Balancing in Cloud Computing Environment 2

A hybrid GWO-PSO Algorithm for Load Balancing in Cloud Compu...

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2nd IEEE International Conference on Green Computing and Internet of Things (ICGCIoT)

作者： Gohil, Bhavesh N. Patel, Dhiren R. SV Natl Inst Technol Comp Engn Dept Surat India

ISBN: (纸本)9781538656570

Cloud computing dynamically allocates virtual resources as per the demands of users. The rapid increase of data computation and storage in cloud computing environment results in uneven distribution of workload on its heterogeneous resources. As a result of that, overloaded servers will have a higher job completion time compared to the corresponding time taken by under loaded servers in the same environment. Distributing balanced workload over the available resources is a key challenge in cloud computing environment. Traditionally, load balancing is used to distribute the workload among multiple servers and to avoid overloading and under loading of servers. It also helps to improve system performance and fair utilization of resources. In this paper, we present a novel hybrid load balancing approach in cloud computing environment using Grey Wolf Optimization based Particle Swarm Optimization and compare it with harmony search, Artificial Bee Colony, Particle Swarm Optimization and Grey Wolf Optimization algorithms. It also helps to improve system performance and fair utilization of resources. Results of research experiments are very encouraging with improved convergence and simplicity.

关键词： Artificial Bee Colony Cloud Computing Grey Wolf Optimization harmony search algorithm Load balancing Particle Swarm Optimization Introduction

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Reconfiguration of Radial Distribution System with Static Load Models for Loss Minimization

Reconfiguration of Radial Distribution System with Static Lo...

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IEEE International Conference on Power Electronics, Drives, and Energy Systems (PEDES)

作者： Kumar, Pawan Singh, Surjit Galgotias Coll Engn & Technol Dept Elect & Elect Engn Greater Noida UP India Natl Inst Technol Dept Comp Sci & Engn Kurukshetra Haryana India

ISBN: (纸本)9781479963737

Loads in distribution system changes with time and weather conditions. With the change in loading conditions power utilities usually reconfigured the network topology for optimal operation. In existing literature, network reconfiguration is performed with constant power load models. However, in real time operation, load characteristics changes with system voltage profile differently. In load modeling, the voltage dependent load has their different voltage exponents. The variation in voltage exponents with change in loading further depends upon the type of load. Therefore, the optimal configuration obtained for specific loading may not be optimum if implemented with change in loading conditions. In this paper, different load models are considered and in order to obtain the optimal configuration harmony search algorithm (HSA) is used. The results are demonstrated on an IEEE 33-node distribution system.

关键词： Distribution System harmony search algorithm Load models Power Loss Reconfiguration

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Optimizing Structure and Internal Unit Weights of Echo State Network for an Efficient LMS-Based Online Training

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Operations Research Forum 2023年第1期4卷 10页

作者： Saadat, Javad Farshad, Mohsen Eliasi, Hussein Department of Electrical and Computer Engineering University of Birjand Birjand Iran

Echo state network (ESN) is a special type of recurrent neural networks (RNN) wherein a dynamic reservoir is used in the hidden layer, the weight of internal units of ESN is kept fix during training process, and output weights are the only trainable weights. Therefore, network training in an offline mode can be changed into a linear regression equation which is simply solved, although it is required to use online training of ESN in some applied problems. The least mean square (LMS) algorithm can provide an easy and constant method for online training of ESN;however, the huge eigenvalue spreads of the correlation matrix of internal network states reduce the speed of the algorithm convergence. In this study, harmony search algorithm (HSA) is used to optimally produce the structure and weight of internal network units. It is possible to significantly reduce the eigenvalue spreads of the correlation matrix of network states by means of this algorithm. Thereafter, the LMS algorithm is used for the online training of ESN built with the help of HSA. Already-obtained simulation results show that the eigenvalue spreads of the correlation matrix are reduced millions of times, and the LMS algorithm increases the online training speed of the network several times with an acceptable precision of training. © 2023, The Author(s), under exclusive licence to Springer Nature Switzerland AG.

关键词： Echo state network harmony search algorithm Least mean square algorithm Prediction and chaotic time series

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A Prediction based Two-Layered Scheduling Approach for Uncertain Scheduling of Hot Strip Mill 8

A Prediction based Two-Layered Scheduling Approach for Uncer...

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8th International Conference on Intelligent Human-Machine Systems and Cybernetics (IHMSC)

作者： Zhong, Huaxing Liu, Min Tsinghua Univ Dept Automat Beijing 100084 Peoples R China

ISBN: (纸本)9781509007684

In this paper, the uncertain scheduling problem of hot strip mill (HSM) is studied, in which the uncertainty of slab supply is considered. We propose a prediction based two-layered scheduling approach (PTLSA) which contains an offline optimization layer and an online adjustment layer. In the offline optimization layer, the arrival probability of each slab group is first predicted by the relevance vector machine (RVM), and then a hybrid harmony search (HHS) algorithm is proposed to generate a predictive rolling round. In the online adjustment layer, if some slab cannot arrive during the execution of the predictive rolling round, an online adjustment rule is designed to select another slab belonging to the same group in order to replace the one cannot arrive. Computational results on industrial data have demonstrated the effectiveness of PTLSA under the uncertain production environment.

关键词： hot strip mill uncertain scheduling relevance vector machine harmony search algorithm

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Sizing and Allocation of Distributed Energy Resources for Loss Reduction using Heuristic algorithms

Sizing and Allocation of Distributed Energy Resources for Lo...

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IEEE Power and Energy Conference at Illinois (PECI)

作者： Sirat, Ali Parsa Mehdipourpicha, Hossein Zendehdel, Niloofar Mozafari, Hamid Missouri Univ Sci & Technol Rolla MO 65409 USA

ISBN: (纸本)9781728152998

Loss minimization in distribution networks (DN) is of great significance since the trend to the distributed generation (DG) requires the most efficient operating scenario possible for economic viability variations. Moreover, voltage instability in DNs is a critical phenomenon and can lead to a major blackout in the system. The decreasing voltage stability level restricts the increase of load served by distribution companies. DG can be used to improve DN capabilities and brings new opportunities to traditional DNs. However, installation of DG in non-optimal places can result in an increase in system losses, voltage problems, etc. In this paper, genetic algorithm (GA), harmony search algorithm (HSA) and improved HSA have been applied to determine the optimal location of DGs. Simulation results for an IEEE 33 bus network are compared for different algorithms, and the best algorithm is stated for minimum losses.

关键词： Distributed Energy Resources Genetic algorithm harmony search algorithm Loss Reduction Radial Distribution System

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Optimization of vehicle delay and drivers' unhappiness at a signalized network: a multi-objective approach 15

Optimization of vehicle delay and drivers' unhappiness at a ...

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IEEE 15th International Conference on Control and Automation (ICCA)

作者： Zhang, Yi Zhang, Yicheng Su, Rong

ISBN: (纸本)9781728111643

In existing system-optimal traffic-responsive signal strategies, the individual driver's interest is always neglected. In order to make a compromise between user equilibrium (individual delay) and system optimality (total delay), a traffic signal scheduling strategy with consideration of drivers' unhappiness is firstly developed based on the cell transmission model (CTM). The exponential function is adopted to delineate the driver's anxiety according to their waiting time, which leads to the assignment of the traffic signals is dominated by drivers' waiting time but not the total volume demand. By adopting the discrete harmony search algorithm (DHS), numerical simulation results illustrate the effectiveness of our real-time traffic light scheduling. Secondly, in order to satisfy the trade-off between the proposed cost (drivers' unhappiness) and the common traffic performance (network delay), a bi-objective urban traffic light scheduling problem by minimizing both the drivers' unhappiness and the total network delay is proposed, which is solved by the non-dominated sorting genetic algorithm II (NSGA-II) and non-dominated sorting harmony search algorithm (NSHS). Experiments are carried out to compare the efficiency of both algorithms.

关键词： urban traffic signal scheduling macroscopic flow model harmony search algorithm NSGA-II

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An Intelligent Method for Breast Cancer Diagnosis Based on Fuzzy ART and Metaheuristic Optimization 14th

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14th Mediterranean Conference on Medical and Biological Engineering and Computing (MEDICON)

作者： Hassani, K. Jafarian, K. Islamic Azad Univ Sci & Res Branch Dept Biomech Tehran Iran

ISBN: (纸本)9783319327037;9783319327013

Breast cancer is one of the major causes of death in women when compared to all other cancers. This cancer has become the most hazardous types of cancer among women in the world. Early detection of breast cancer is essential in reducing life losses. In this paper some metaheuristic optimization algorithms was used to find the parameters of the Fuzzy-ART. Fuzzy-ART is not so strong to deal with above data. However, its performance is significantly improved by using evolutionary optimization methods. These hybrid classification techniques were tested on a training data set provided by the Wisconsin dataset for breast cancer. Results showed that the proposed harmony search (HS) algorithm provides better result with less time and less number of steps than genetic algorithm (GA) and particle swarm optimization (PSO) in the same conditions. As seen in this research, evolutionary HS algorithm had a higher convergence ability to obtain optimal solution too. The best performance obtained from this algorithm is 97.80% for accuracy and 98.92% for specificity.

关键词： Breast Cancer Diagnosis Fuzzy-ART Metaheuristic Optimization Genetic algorithm Particle Swarm Optimization harmony search algorithm

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