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Sensor device scheduling-based cuckoo algorithm for enhancing lifetime of cluster-based wireless sensor networks

INTERNATIONAL JOURNAL OF COMPUTER APPLICATIONS IN TECHNOLOGY 2022年第1期68卷 58-69页

作者： Hameed, Mazin Kadhum Idrees, Ali Kadhum Univ Babylon Dept Software Babylon Iraq Univ Babylon Dept Comp Sci Babylon Iraq

This study proposes the Sensor Device Scheduling-based cuckoo algorithm (SeDeSCA) for enhancing the lifespan of cluster-based WSNs. SeDeSCA consists of two phases: clustering and scheduling. The WSN is clustered into clusters using the DBSCAN algorithm in the first phase. The scheduling phase is periodic and consists of three steps: cluster head polling, scheduling decision-based optimisation, and covering. The sensors in each cluster choose their cluster head, which executes the cuckoo algorithm (CA) to select a suitable schedule of sensors that will achieve sensing during the current period. The aim of scheduling is to minimise energy consumption and ensure sufficient coverage for the monitored area while maximising network lifespan. The third step is to cover the area of interest with the sensors that are scheduled to be active during this period. The simulation results show that SeDeSCA improves the network lifespan and coverage ratio, as well as the lifespan of WSNs.

关键词： wireless sensor networks cuckoo algorithm DBSCAN lifetime enhancement scheduling algorithms

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Optimum Setting Parameters of Multiple Tuned Mass Damper for Passive Control of Structures Using cuckoo algorithm

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IRANIAN JOURNAL OF SCIENCE AND TECHNOLOGY-TRANSACTIONS OF CIVIL ENGINEERING 2023年第3期48卷 1-14页

作者： Jafarinia, Hamid Ostad-Ali-Askari, Kaveh Islamic Azad Univ Dept Civil Engn Khorramabad Branch Khorramabad *** Iran Amer Univ Dubai Sch Engn Dept Civil Engn POB 28282 Dubai U Arab Emirates Isfahan Univ Technol Coll Agr Dept Water Engn Esfahan *** Iran

Adjustable mass dampers are widely used to reduce the seismic vibrations of engineering structures. The efficiency of these systems requires a proper setting of its parameters. In this study, an efficient and effective method for designing optimal multi-tuned mass dampers (MTMD) is proposed to reduce the vibration response of structures, which is based on the definition of a multi-objective optimization problem. Therefore, the multi-objective optimization algorithm of the cuckoo has been used to solve the issue. MTMD setting parameters are considered as design variables. Since the setting of MTMD parameters is basically a multi-objective optimization problem, three objective functions including minimizing the maximum displacement of the roof, the maximum acceleration of the roof and the maximum displacement of TMDs have been considered in the optimization problem. The results of numerical simulations for a ten-story shear frame exposed to an earthquake show that the cuckoo multi-objective optimization algorithm is able to find appropriate solutions in the form of Parreto curves to set the optimal parameters of MTMDs according to the design objectives. Provided that they are caused by creating a suitable compromise between the objective functions in conflict with each other. Therefore, MTMDs reduce the seismic responses of the structure in a favorable way. Based on the results, it was found that MTMD performance depends on incoming earthquake, TMD mass ratio and number of TMDs. By increasing the number of TMDs, up to a certain limit (10), the seismic response of the seismic system is reduced in a favorable way, but many changes in reducing the seismic response of the structure are not observed. Also, the seismic response of the system is reduced to a certain value (6%), by increasing the mass ratio of TMDs, but the process of reducing the seismic response of structures does not undergo many changes with its further increase.

关键词： Passive control of structures Multiple adjusted mass damper Multi-objective optimization cuckoo algorithm Multi-tuned mass dampers Seismic vibrations Engineering structures Numerical simulations Parreto curves Design objectives Earthquake

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Optimal Overcurrent Relays Coordination in Microgrid Using cuckoo algorithm 3

Optimal Overcurrent Relays Coordination in Microgrid Using C...

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3rd International Conference on Power and Energy Systems Engineering, (CPESE)

作者： Ahmarinejad, Amir Hasanpour, Seyed Mohsen Babaei, Mojtaba Tabrizian, Mohammad Islamic Azad Univ Dept Elect Engn Yadegar E Imam Khomeini RAH Shahr E Rey Branch Tehran Iran

Microgrid(MG) is a controlled branch of Distributed Generations(DGs) and loads in distribution network and offers more potential in DGs operation and control. MG can operate with and without utility grid (Island mode). The operation of this system in islanded mode requires sophisticated control and protection schemes. MG protection should be capable of fault detection with appropriate sensitivity and selectivity in both rigid-connected and islanded modes. This paper presents solving the issue of short circuit level difference in both modes using fault current limiter (FCL). Overcurrent(O/C) relays coordination and fault current limiter impedance are selected in such a way that protection system has a suitable operation for both modes. For this purpose, artificial intelligence methods of Particle Swarm Optimization (PSO) algorithm and cuckoo algorithm have been used to achieve optimal relays coordination and fault current limiter impedance. The under study grid is a small MG related to Tehran Oil Refinery and the simulations have been running using MATLAB. The results indicate that fault current limiter can be used to solve the problem of short current level difference in both modes and cuckoo algorithm is a more effective method for optimization applications. (C) 2016 The Authors. Published by Elsevier Ltd.

关键词： Microgrid Overcurrent Relays Fault Current Limiters cuckoo algorithm Particle Swann Optimization algorithm

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Minimizing Excessive Handover Using Optimized cuckoo algorithm in Heterogeneous Wireless Networks 2nd

Minimizing Excessive Handover Using Optimized Cuckoo Algorit...

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2nd International Conference on Computer and Communication Technologies

作者： Kumar, Salavadi Ananda Murthy, K. E. Sreenivasa Jawaharlal Nehru Technol Univ Hyderabad Andhra Pradesh India Adishankara Coll Engn & Technol Nellore India

ISBN: (纸本)9788132225263;9788132225256

In this paper we worked out to find the best solution for the two constraints in heterogeneous wireless environments: finding the best available network in a reasonable amount of time with optimized parameter values (such as cost of network should be minimum) and try to minimize the number of handovers, when mobile node is moving by overlapping of different wireless networks provided by different network providers. Here the decision problem is formulated as multiple objective optimization problems and simulated using cuckoo optimizing algorithm. In this paper our simulation result shows that the number of handovers can be minimized if we take optimized network parameter values.

关键词： Vertical Handoff cuckoo algorithm Number of handovers Heterogeneous network Best network Parameter optimization

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MODCSA-CA: A multi objective diversity controlled self adaptive cuckoo algorithm for protein structure prediction

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GENE REPORTS 2017年 8卷 100-106页

作者： Ramyachitra, D. Ajeeth, A. Bharathiar Univ Dept Comp Sci Coimbatore Tamil Nadu India

Finding the native structure of a protein initially from its amino acid sequence remains one of the most challenging open problems in Bioinformatics and molecular biology. Protein structure prediction plays a critical part in protein construction and mapping analysis, drug design and any other biological applications. Extracting good representation from protein sequence is fundamental to this prediction task. The multi-objective optimization tends to be more effective than other techniques in complex problems. The protein structure prediction problem is solved using Diversity Controlled Self-Adaptive cuckoo algorithm. MODCSA-CA, an improved version of Self-Adaptive Differential Evolution (SaDE), to check the diversity of individuals and local search to sustain a balance between exploration and exploitation. This subject looks into the application of cuckoo search (CS) algorithm on the protein structure prediction problem. Results point MODCSA-CA as a competitive approach for total energy and conformation similarity metrics. Comparability of the statistical results demonstrates that CS outperforms other algorithms in a meaningful manner.

关键词： Protein structure prediction cuckoo algorithm Levy flight Angle Optimization

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A Control Method Based on Improved cuckoo algorithm for Photovoltaic Hybrid Hydrogen Production System 9

A Control Method Based on Improved Cuckoo Algorithm for Phot...

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9th International Conference on Power and Renewable Energy

作者： Sun, Ziqi Peng, Yunfeng Zhang, Dongdong Shanghai Jiao Tong Univ Sch Elect Informat & Elect Engn Shanghai Peoples R China Guangxi Univ Sch Elect Engn Nanning Peoples R China

ISBN: (纸本)9798350377477;9798350377460

In view of control issues associated with renewable energy hydrogen production systems, this study focuses on the hybrid hydrogen production system consisting of a photovoltaic-ALK+PEM electrolyzers and proposes a power control strategy based on the improved cuckoo algorithm. By implementing this control method in the DC-DC converters of electrolyzers, the system achieves stable operation and rapid convergence of DC bus voltage. Compared to PI control, the control scheme based on the improved cuckoo algorithm comprehensively enhances the system's performance, ensuring swift stability of DC bus voltage and precise control outcomes. This proposed method not only realizes coordinated control of multiple types of electrolyzers, but also considers the system's rapid response capability and anti-interference ability during the entire process.

关键词： cuckoo algorithm hybrid hydrogen production system DC-DC converter coordinated control for electrolyzers

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Speech classification based on cuckoo algorithm and support vector machines 2

Speech classification based on cuckoo algorithm and support ...

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2nd IEEE International Conference on Computational Intelligence and Applications (ICCIA)

作者： Shi, Wenlei Fan, Xinhai Acad Armored Forces Engn Dept Mech Engn Beijing Peoples R China

ISBN: (纸本)9781538620304

Speech classification is an important part of speech signal processing. It is significant to classify speech accurately and quickly in speech coding and speech synthesis. Because of the diversity and uncertainty of the speech signals, the traditional classification method is slow and not so accurate in the large-scale application of real speech classification. In order to improve the accuracy and precision of speech classification, a speech classification method based on support vector machine optimized by cuckoo algorithm(CS-SVM) is proposed. Firstly, choose four types of music: folk songs, Guzheng, rock and pop. And adopt the cepstral coefficient to extract speech feature, then use the support vector machine optimized by the cuckoo algorithm to train the characteristic signals, and establish the optimal classifier model, and finally classify the tested speech. The results of the simulation experiment show that the support vector machine based on the cuckoo algorithm(CS-SVM) is better than the traditional SVM and BP neural network in speech recognition.

关键词： support vector machine cuckoo algorithm speech classification classification model BP neural network

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Multi-objective optimization method of smart medical wireless sensor network coverage based on improved cuckoo algorithm 3

Multi-objective optimization method of smart medical wireles...

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2023 IEEE 3rd International Conference on Data Science and Computer Application, ICDSCA 2023

作者： Xu, Zhen Chen, Ping Jiangxi Science and Technology Normal University Nanchang China

ISBN: (纸本)9798350341546

In order to improve the coverage level of smart medical wireless sensor network, a multi-objective optimization method of smart medical wireless sensor network coverage based on improved cuckoo algorithm is proposed. Construct the routing node deployment structure model of smart medical wireless sensor network, adopt the channel balanced scheduling method to realize the structured scheduling and spread spectrum processing of the transmission layer of smart medical wireless sensor network, adopt the multi-sensor fusion tracking identification method to realize the identification of the coverage parameters of smart medical wireless sensor network, adopt the improved cuckoo algorithm to establish the dynamic distribution function of wireless sensor network coverage multi-objective optimization, and randomly scatter several sensors in the area to be monitored. And set a certain number of anchor nodes, initialize the position parameters of the population, calculate the fitness value of the initial population and sort it from small to large. Through the joint parameter identification of the initial position set and the target position set of the mobile node, the multi-objective optimization of the coverage of the smart medical wireless sensor network is realized. The simulation test results show that this method can improve the coverage level of nodes and reduce the network energy cost and transmission error rate. © 2023 IEEE.

关键词： Coverage cuckoo algorithm Multi-objective optimization Smart medical wireless sensor network

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Short-term Wind power Prediction Model Based on cuckoo algorithm and BP neural Network

Short-term Wind power Prediction Model Based on Cuckoo Algor...

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2020 Asia Energy and Electrical Engineering Symposium

作者： Zhu, Chengming Wei, Yunbing Zhu, Jianan Jiang, Chengcheng Shanghai Univ Engn Sci Sch Elect & Elect Engn Shanghai Peoples R China

ISBN: (纸本)9781728167824

Aiming at the shortcomings of existing accurate prediction methods of wind power generation, a prediction model combining cuckoo algorithm and BP neural network is proposed. The optimal solution obtained by the cuckoo algorithm is used to assign the initial weight and threshold value of the BP neural network, and the historical power generation data is trained, and then the wind power is predicted by the BP neural network. In this paper, the actual wind power generation in Belgium is taken as an example to compare and analyze the error between BP neural network based on cuckoo algorithm and common BP neural network, BP neural network based on particle swarm optimization algorithm and BP neural network based on Genetic algorithm in wind power generation prediction. The experimental results show that the improved BP neural network model based on the cuckoo algorithm has better nonlinear fitting ability and higher accuracy than the other three network models for wind power prediction.

关键词： wind power generation cuckoo algorithm BP neural network prediction model

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Research on the control of multi-conditions energy storage plant based on cuckoo algorithm 5

Research on the control of multi-conditions energy storage p...

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5th International Conference on Power and Energy Technology, ICPET 2023

作者： Huang, Jieming Huang, Xiaorong Zhang, Qingbo Zhong, Rongfu Lai, Rijing Luo, Junjie Dongguan Power Supply Bureau of Guangdong Power Grid Corporation Guangdong Dongguan China

ISBN: (纸本)9798350339673

Energy storage technology can provide a variety of services for grid operation, such as peak regulation, frequency regulation, standby, startup, demand response, etc. However, considering that energy storage plants operate under multiple operating conditions, the peak regulation and valley filling of the power grid are unstable, and it is impossible to take into account the charging and discharging depth of energy storage plants and the decay of energy storage battery life and its capacity, so the original single charging and discharging control method can hardly meet the demand. The paper proposes an improved strategy of cuckoo algorithm for multiple operating conditions, and proves through experimental results that after considering the multi-operating conditions control strategy, the optimal configuration can be made by integrating all the operating conditions of the energy storage plant and the characteristics of the grid tide, which is superior to the actual operation of the original energy storage plant. © 2023 IEEE.

关键词： cuckoo algorithm Energy storage Grid peaking Multiple operating conditions Power Grid

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