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检索条件"主题词=whale optimization algorithms"

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An Interoperability Test Case Generation Method for State Transition and Parameter Combination Coverage

An Interoperability Test Case Generation Method for State Tr...

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Frontiers Technology of Information and Computer (ICFTIC), IEEE International Conference on

作者： Changan Wei Ji Xu Zhong Bo Yunlong Sheng Feixuan Wang School of Electronics and Information Engineering Harbin Institute of Technology Harbin China

ISBN: (数字)9798331541750

ISBN: (纸本)9798331541767

This paper addresses the critical role of interoperability testing for launch and control electronic information systems and introduces a novel test case generation method leveraging the whale optimization Algorithm (WOA). With the increasing complexity of launch missions, ensuring seamless coordination between these systems is of paramount importance. By constructing state transition models and optimizing parameter combinations, WOA can efficiently generate high-coverage test cases that validate system interoperability. Experimental results demonstrate that WOA significantly outperforms traditional algorithms, such as Particle Swarm optimization (PSO) and Genetic Algorithm (GA), in terms of the number of test cases generated, convergence speed, coverage rate, and fitness value. This method presents a robust solution for enhancing the testing efficiency and reliability of launch and control electronic information systems in the context of complex mission scenarios.

关键词： Reliability theory Control systems Solids whale optimization algorithms Particle swarm optimization Interoperability Testing Information systems Genetic algorithms Convergence

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Secure and Efficient Data Transmission for IoT Devices in Untrusted Environments

Secure and Efficient Data Transmission for IoT Devices in Un...

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Distributed Systems, Computer Networks and Cybersecurity (ICDSCNC), International Conference on

作者： Upma Jain Smitha K R.S.S. Raju Battula Arindam Sarkar Natasha Martin Natrayan L Department of Computer Science & Engineering Graphic Era Deemed to be University Dehradun India Department of Artificial Intelligence and Machine Learning BGS Institute of Technology Adichunchanagiri University India Department of Computer Applications Aditya University India Department of Applied Electronics and Instrumentation Engineering Heritage Institute of Technology Kolkata India Department of Law Symbiosis Law School Symbiosis International (Deemed University) Pune India Department of Mechanical Engineering Saveetha School of Engineering SIMATS India

ISBN: (数字)9798350375442

ISBN: (纸本)9798350375459

One technological trend that will not go away in the modern world is the Internet of Things (IoT). With the development of the Internet of Things, the world is becoming smarter. The efficacy, flexibility, and simplicity of deployment of IoT make it the preferred choice for most real-time applications. But energy efficiency and security are the big obstacles for the Internet of Things. Presented here are safe, energy-efficient solutions for the Internet of Things (IoT), a problem whose significance this study acknowledges. Since routing is the primary energy consumer, this study presents secure routing strategies that are both energy efficient and reliable. Three distinct safe data transmission techniques for the Internet of Things (IoT) are presented in this paper, all of which aim to reduce energy usage during routing. The first part of this study lays out a clustering-and secure route selection-based architecture for safe and energy-efficient data transmission with the Internet of Things (IoT). The W-HHO technique, which is based on whale optimization, is used to identify the secure routes, and fuzzy-based secure clustering is used for that purpose. Encryption protocols that work in tandem with cypher block chaining ensure the safety of sensitive information. Using industry-standard metrics like packet delivery rate, throughput, energy efficiency, network longevity, etc., we assess how well each solution performs. When compared to the current methods, the outcomes produced by the presented works demonstrate promising performance.

关键词： Performance evaluation Software algorithms Clustering algorithms Routing Throughput Energy efficiency whale optimization algorithms Routing protocols Internet of Things Data communication

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Investigations of PAPR reduction methods in FBMC System

Investigations of PAPR reduction methods in FBMC System

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Intelligent and Innovative Technologies in Computing, Electrical and Electronics (IITCEE), International Conference

作者： Rashmi Rani Samantaray Siddappaji Department of Electronics and Communication VTU HKBK College Of Engineering Bengaluru India Department of Electronics and Communication BMS College of Engineering Bengaluru India

ISBN: (数字)9798331515911

ISBN: (纸本)9798331515928

The primary concern of the 5G radio network has sparked interest in the development of new waveforms beyond 4G (5th generation networks). Filter Bank Multicarrier (FBMC) waveforms have recently been suggested as the desired one for 5G networks. It has both advantages and disadvantages. One of the biggest drawback of the FBMC broadcast signal is its high Peak to Average Power Ratio (PAPR). It has been widely used in wireless communication to achieve high speed and data rates. A high PAPR system results in substantial distortion of the signal because of the nonlinear power amplifier. Therefore, methods that effectively reduce PAPR are necessary for the realization of the FBMC system. The FBMC system uses the some common techniques as the OFDM system. Comparative analysis of various approaches such as PTS, SLM, Companding, etc are performed by considering their simulation outcomes when it comes to effective spectrum utilization, improved PAPR, along with minimum complexity.

关键词： Wireless communication 5G mobile communication Nonlinear distortion Metaheuristics Power amplifiers Peak to average power ratio whale optimization algorithms Complexity theory Radio networks Particle swarm optimization

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Design and Analysis of an Adaptive QoS Aware Approach for Supporting Multiple Services using Meta Heuristic Enhanced whale optimization Algorithm over Hybrid Cloud Environment (EWOC)

Design and Analysis of an Adaptive QoS Aware Approach for Su...

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Automation, Computing and Renewable Systems (ICACRS), International Conference on

作者： Premnadh Katkam P. Anbalagan V.V.S.S.S. Balaram Department of Computer Science and Engineering Annamalai University Annamalainagar Dept. of Computer Science and Engineering Annamalai University Annamalainagar Sreenidhi Institute of Science and Technology Yamnampet Ghatkesar Hyderabad

ISBN: (纸本)9781665460859

Though numerous research works have discussed about approaches towards providing QoS over cloud environment for variable services, research community suggest that the need for an adaptive QoS approach with quantifiable resources is a challenge. Hybrid cloud is currently adopted by industry with need for consistent QoS and variable security features. Variable number of users connected over cloud demand consistent resources such as network link capacity, distributed storage and dynamic processing capabilities for execution of service based on variable cloud. This paper focuses on identification and provisioning of demandable resources over a session for a specific task. The proposed EWOC approach works on an enhanced whale optimization algorithm for QoS supportive sessions in use. This paper models an adaptive resource assignment over PSO, SA scheduling algorithms and their QoS aspects.

关键词： Adaptation models Scheduling algorithms Heuristic algorithms Quality of service Throughput whale optimization algorithms Delays

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Chaotic-Opposition whale optimization algorithm based load flow analysis of small-scale, median and broad critical power systems

Chaotic-Opposition Whale optimization algorithm based load f...

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Power and Renewable Energy Conference (IPRECON), IEEE International

作者： Suvabrata Mukherjee Provas Kumar Roy Dept. of Electrical Engineering Kalyani Government Engineering College West Bengal India

In power system phraseology load flow study deals with attainment of steady state explication of the power network and determined for steady state powers for various buses along with the bus voltages. For adhering to the load flow problem, a modified version of whale optimization Algorithm has been suggested by the authors in this paper. The algorithm is a trustworthy meta-heuristic optimization algorithm derived from nature and motivated by the humpback whale bubble-net hunting hypothesis. The accuracy and reliability has been enhanced by the introduction of chaos theory and opposition-based learning (OBL) to WOA so as to effectively cover the entire search region and thereby enhance the convergence of single or multi-objective metaheuristic algorithms. The new algorithm termed as Chaotic-Opposition based whale optimization (COWOA) uses the chaos theory for primary tuning of parameters of WOA by which the exploitation and exploration processes are adjusted and OBL is used to look for the solutions in reverse direction of indicated values in order to test if selects in reverse direction can provide even better solutions. Numerical and simulation results demonstrate that in discerning scenario when traditional load flow approaches flounder, COWOA is able to provide effective solutions.

关键词： Simulation Metaheuristics whales Power system stability Reliability theory whale optimization algorithms Robustness

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Single neuron adaptive control and parameter optimization of lower limb rehabilitation exoskeleton

Single neuron adaptive control and parameter optimization of...

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IEEE Conference on Industrial Electronics and Applications (ICIEA)

作者： Zhirui Li Wenjie Chen Xiantao Sun Weihai Chen Zaojun Fang Guilin Yang School of Electrical Engineering and Automation Anhui University Hefei China School of Automation Science and Electrical Engineering Beihang University Beijing China Ningbo Institute of Materials Technology and Engineering Chinese Academy of Sciences Ningbo China

ISBN: (纸本)9781665409858

For the bottom position control of the lower limb exoskeleton robot driven by DC motor, a single neuron adaptive control method with parameters selected by the improved whale optimization algorithm is proposed. Since the parameter tuning process existing in traditional control is cumbersome and it is difficult to achieve optimal control accuracy, we present a single neuron adaptive controller to improve the control accuracy. In addition, in order to complete the optimal selection of controller parameters, the whale optimization algorithm is used to select parameters, this algorithm is improved, and the optimization simulation results are displayed. Finally, an adaptive underlying controller is designed, and the simulation results are compared with the traditional PID control. The results show that, compared with the traditional method, the single neuron adaptive control with the optimized parameters of the improved whale optimization algorithm has better control effect.

关键词： PI control Simulation Neurons Exoskeletons Sociology whale optimization algorithms PD control

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Optimal DG Allocation Based on Pay-back Period by a Proposed Modification for Coronavirus Herd Immunity optimization

Optimal DG Allocation Based on Pay-back Period by a Proposed...

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International Middle-East Power System Conference, MEPCON

作者： Tarek A. Boghdady Elsayed Tag Eldin Howaida M. Ragab Ahdab Elmorshedy Electric Power Engineering Dept. Cairo University Giza Egypt Faculty of Engineering and Technology Future University in Egypt New Cairo Egypt Electric Power Engineering Dept. Ahram Canadian University Giza Egypt

ISBN: (纸本)9781665463645

Distribued Generations (DG) have economic, financial, and environmental benefits. DG reduces power losses in the distribution system but has a negative impact on the protection devices. In this article, the IEEE 33 bus system will be used and tested by adding up to three DG units using MATLAB/SIMULINK software. the optimization techniques that will be used are Grey Wolf Optimizer, whale optimization Algorithm, Genetic Algorithm, and Coronavirus Herd Immunity or COVID-19 optimization techniques to select the optimal site and size of the DG units based on the lowest pay-back period considering the voltage limits and power losses. The paper proposes a modified mutation operator for COVID-19 based on Gaussian and Cauchy mutations to have better performance and lower variance. The proposed algorithm is compared with the other optimization techniques. The proposed algorithm achieved better results, which proved to have competitive performance with state-of-the-art evolutionary algorithms.

关键词： COVID-19 Costs Software algorithms Voltage Linear programming whale optimization algorithms Software

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Using Modified whale optimization Algorithm for Solving Traveling Salesman Problem

Using Modified Whale Optimization Algorithm for Solving Trav...

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Artificial Intelligence of Things (ICAIoT), International Conference on

作者： Ali Abdullah Saleh Mesut Çevik Electrical and Computer Engineering Altinbas University Istanbul Turkey

The main problem of the network is that the wrong designs and incorrect connection lead to major problems such as cost impact problems and network efficiency, the most famous being Fiber Optical network problems that still considered a problem for various types of networking. Travel Salesmen’s Problem (TSP) is one of the most traditional methods for solving this type of problem, depending today on optimization. Modified algorithms may be regarded as one of the most resourceful and effective ways to solve animal-based TSP problems. whale optimization Algorithm (WOA) and Genetic Algorithm (GA) focuses this paper on TSPLIB-type issues. This work showed a greatly promising performance with whale optimization Algorithm and was better than the genetic algorithm.

关键词： Costs Optical fiber networks Traveling salesman problems whale optimization algorithms Internet of Things Artificial intelligence optimization

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optimization of Contactless Distribution in the Post-COVID Era

Optimization of Contactless Distribution in the Post-COVID E...

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IEEE International Conference on Intelligent Transportation Engineering (ICITE)

作者： Yang Zhang Jiacheng Li Lei Li Graduate School of Science and Engineering Hosei University Tokyo Japan Department of Electrical Electronics and Information Engineering Kanagawa University Yokohama Japan

During an emergency, timely and effective distribution of emergency supplies is critical in rescue. In the context of Covid-19, given the difficulties in distributing supplies to communities due to super infectious viruses, unmanned vehicle distribution is studied by taking into account the priority and satisfaction of communities to improve distribution safety and effectiveness of supplies. Furthermore, the influence of distribution time on the overall efficiency is also taken into account, thus ultimately establishing an unmanned distribution model with the shortest distribution time while meeting community satisfaction. The improved whale algorithm is used to solve the dual-objective model and compared with the basic whale optimization algorithm. The results show that the improved whale algorithm demonstrates better convergence, searchability, and stability. The constructed model can scientifically distribute daily necessities to communities while considering their priority and satisfaction.

关键词： COVID-19 whales Transportation Stability analysis whale optimization algorithms Safety Planning

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Designing an Efficient Product Image Classification Framework Using Adaptive YoloV5 with Long Short-Term Memory in E-Commerce Platform

Designing an Efficient Product Image Classification Framewor...

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Cognitive Computing in Engineering, Communications, Sciences and Biomedical Health Informatics (IC3ECSBHI), International Conference on

作者： Munmi Dutta Amrita Ganguly Department of Electrical Engineering Assam Engineering College Guwahati Assam India

ISBN: (数字)9798331518523

ISBN: (纸本)9798331518530

Presently, the online store supports the customers to buy the desired products in online. So, huge competitions are developed in the Electronic Commerce (E-commerce) sector for developing the technology. Most of the E-commerce platforms represent the particular products that users enquire about and also display other similar objects also to improve the interest among the online customers. As the online platforms hold more variety of products, it is essential to analyze the similar products sold together, and also its recommendation is needed. Sentimental analysis plays a major role in opinion mining, which helps to enhance product recommendations to online users. Every day enormous data are generated in the E-commerce and the data are utilized by online retailers to identify customer expectations. Using enormous resources, sentimental analysis models process multiple online options. Hence, it is important to construct a new product image classification technique for the E-commerce platform by considering the limitations of existing techniques. At first, essential images are acquired from standard sources. The gathered images are provided to the product image classification phase. Here, effective product image classification procedures are executed using a developed framework named Adaptive YoloV5 with Long Short-Term Memory (A-YoloV5-LSTM). Also, the weights and hyper-parameters are tuned using Beluga whale optimization (BWO). Further, the efficiency of the recommended product image classification technique is validated over different performance metrics.

关键词： YOLO Deep learning Accuracy Neurons Feature extraction whale optimization algorithms Electronic commerce Long short term memory Standards Image classification

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