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检索条件"主题词=Whale Optimization Algorithms"

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An Interference Mitigation Method via Variable Separation Angle between LEO Constellations

An Interference Mitigation Method via Variable Separation An...

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International Conference on Wireless Communications and Signal Processing (WCSP)

作者： Yuxin Peng Jiansong Miao Fuhao Liu School of Information and Communication Engineering Beijing University of Posts and Telecommunications Beijing China

ISBN: (数字)9798350390643

ISBN: (纸本)9798350390650

With a large number of satellites in orbit, there is an inevitable problem of co-frequency interference between low earth orbit (LEO) satellite constellations. However, existing studies tend to focus on avoidance strategies with a constant angle, ignoring the positional relationship between satellites and earth stations. In this paper, our work is to study the interference mitigation strategy between LEO constellations and propose a variable separation angle method based on different positional relationships while selecting the optimal separation angle in each case. Moreover, given the satellite capacity, the joint optimal problem of minimum separation angle and maximum channel capacity is established and solved by the whale optimization algorithm (WOA) for its better convergence speed and stability with respect to other algorithms. Meanwhile, the separation angle strategy is applied to interference simulation based on Oneweb and Lightspeed. Compared to the fixed separation angle strategy, the simulation results prove the method improves the system performance in terms of interference power, information rate, and interference time.

关键词： Wireless communication Satellites Channel capacity Prevention and mitigation System performance Noise Low earth orbit satellites Signal processing algorithms Interference whale optimization algorithms

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Decoupling Method for Six-Axis Force Sensors Based on WOA-ELM

Decoupling Method for Six-Axis Force Sensors Based on WOA-EL...

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Robotics & Intelligent Manufacturing Technology (ISRIMT), International Symposium on

作者： Jing Chen Lijun Meng Haoqi Xu Zhenhao Wu State Key Laboratory of Precision Blasting Jianghan University Wuhan China

ISBN: (数字)9798331528942

ISBN: (纸本)9798331528959

The coupling problem between the six dimensions of force sensors seriously affects the improvement of measurement accuracy. To address this issue, this study focuses on the strain-based six-axis force sensor with a six-beam structure. The whale optimization algorithm (WOA) is used to optimize the input weights and hidden layer thresholds of the extreme learning machine (ELM) model, and a decoupling algorithm is proposed. The research results show that after decoupling, both Type I and Type II errors are controlled within 0.3%, effectively improving the measurement accuracy of the six-axis force sensor. Compared with other prediction models (Least Squares, BP neural network, and ELM), the WOA-ELM model proposed in this paper has significant improvements in prediction accuracy, decoupling time, and generalization ability.

关键词： Accuracy Force measurement Extreme learning machines Predictive models Prediction algorithms whale optimization algorithms Stability analysis Real-time systems Force sensors Biological neural networks

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Optimal Target Interception using Foldable Quadrotor with Rotating Arms

Optimal Target Interception using Foldable Quadrotor with Ro...

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International Conference on Image and Signal Processing and their Applications (ISPA)

作者： Zakaria Mehal Yasser Bouzid Mohammed Guiatni Saddam Hocine Derrouaoui Complex Systems Control and Simulators (CSCS) Laboratory Ecole Militaire Polytechnique Bordj el Bahri Algeria Ecole Superieure Ali Chabati Algires Algeria

ISBN: (数字)9798350309249

ISBN: (纸本)9798350309256

This article addresses a critical problem in the field of target interception using a new foldable quadrotor with rotating arms. The primary challenge is maximizing linear acceleration to enhance the quadrotor’s ability to intercept targets effectively. To address this challenge, we introduce a novel optimization framework. Our study employs two distinct optimization algorithms, namely the genetic algorithms and the whales optimization algorithm, to ascertain the maximum attainable linear acceleration for the foldable quadrotor. The results obtained are confirmed through the use of our innovative foldable quadrotor.

关键词： Heuristic algorithms Signal processing algorithms Life estimation Signal processing whale optimization algorithms optimization Robots

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Optimal Energy Storage Configuration Method For Wave Energy Power Generation System

Optimal Energy Storage Configuration Method For Wave Energy ...

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Energy Engineering and Power Systems (EEPS), International Conference on

作者： Lixin Wang Ye Li Shuai Yang Wenbin Hei Yating Chen Xiaoting Ma Inner Mongolia Power Group Hohhot China Inner Mongolia Electric Power Economics and Technology Research Institute Hohhot China

ISBN: (数字)9798350375138

ISBN: (纸本)9798350375145

The rapid and random changes in wave characteristics make it difficult to meet the requirements for secure and stable operation of the power grid, resulting in low wave energy utilization. The inherent advantage of energy storage can address the grid connection and improve wave energy consumption, hence proposing an energy storage optimization configuration method for wave energy generation system. The goal is to minimize the construction and operational costs of the wave energy storage system by taking into account constraints such as the state of charge of the energy storage, energy storage power, and the grid operating conditions. An energy storage configuration optimization model is established. The whale optimization Algorithm and Genetic Algorithm are applied to solve the inner and outer layer models, optimizing the system's daily operation strategy, energy storage access points, and capacity to increase wave energy utilization while minimizing system costs. Simulation results show that in the IEEE 33-node system, the proposed method can address the energy storage layout, and capacity configuration issues in wave energy power generation system(WEPGS), verifying the effectiveness and feasibility of the proposed method.

关键词： Costs optimization models Simulation whale optimization algorithms State of charge Wave energy conversion optimization Power generation Energy storage Genetic algorithms

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UAV-enabled Secure Communication Under Marine Imperfect Channel Based on Collaborative Beamforming

UAV-enabled Secure Communication Under Marine Imperfect Chan...

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IEEE Symposium on Computers and Communications (ISCC)

作者： Yuqing Liu Fang Mei Geng Sun Hui Kang Xinrong Guo College of Software Jilin University Changchun China College of Computer Science and Technology Jilin University Changchun China

ISBN: (数字)9798350354232

ISBN: (纸本)9798350354249

With the widespread use of unmanned aerial vehicles (UAVs), the issue of data confidentiality is becoming more and more prominent. For this reason, this paper intends to build a UAV-enabled virtual antenna array (UVAA) and communicate with the BS on a vessel in a maritime environment using cooperative beamforming (CB) techniques. To improve safety, the UAV elements can carry optimal excitation current weights and fly to appropriate locations for CB transmission. However, this will result in more energy consumption. To address several critical issues in UAV communication, a secure communication multi-objective optimization problem (SCMOP) is proposed to simultaneously improve the total secrecy rate, the total maximum sidelobe levels (SLLs), and the total motion energy consumption of the UAVs by jointly optimizing the position and the excitation current weights. Because the SCMOP is non-convexity and NP-hard, we adopt a non-dominated sorting whale optimization algorithm(INSWOA) with chaotic solution initialization, optimal position update based on the sine cosine algorithm (SCA), and adaptive weights to solve the problem. Experiments show that this method can better solve the SCMOP and is superior to some existing standard methods.

关键词： Energy consumption Chaotic communication Array signal processing Collaboration Autonomous aerial vehicles whale optimization algorithms Standards optimization Antenna arrays Sorting

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The Multi-energy Interconnected Power System Based on the CPS Standard Cooptimizes the Load Frequency Control

The Multi-energy Interconnected Power System Based on the CP...

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Power and Electrical Engineering (ACPEE), 5th Asia Conference on

作者： Li Dianyang Wang Mingkai Zhan Keming Li Jiaze Zhu Guangyu State Grid Liaoning Electric Power Co. LTD Shenyang China

ISBN: (数字)9798350309638

ISBN: (纸本)9798350309645

Aiming at the regulation characteristics of multi-energy interconnected power system based on provincial CPS standard, this paper proposes a heuristic intelligent optimization algorithm to assist the cooperative optimization frequency control method of multi-energy interconnected power system based on CPS standard, which takes the regional control deviation of each region as the objective function. The parameters of PID load frequency controller in each region are optimized cooperatively, so that the system can maintain frequency stability and long-term safe operation of the system based on CPS standard under various random disturbances. Finally, a multi-energy three-area interconnected power system model based on CPS standard is established. The frequency stability of the system under different optimization setting methods and the stability of each regional system under different disturbances are compared, and the effectiveness of the method is verified. The results show that the cooperative optimization tuning method of multi-area interconnected load frequency controller based on CPS standard effectively improves the stability of the system, and has good robustness and practicability.

关键词： Time-frequency analysis Simulation Power system stability Stability analysis Robustness whale optimization algorithms Standards

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Research on Monthly Precipitation Prediction Model Based on WOA-CEEMDAN-BiLSTM

Research on Monthly Precipitation Prediction Model Based on ...

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Internet of Things, Automation and Artificial Intelligence (IoTAAI), International Conference on

作者： Yong Fang Menchita Dumlao Joey Aviles Graduate School Angeles University Foundation Angeles City Philippines Dongguan City University Dongguan China Philippine Women's University Manila City Philippines

ISBN: (数字)9798350386974

ISBN: (纸本)9798350386981

In order to further improve the accuracy and generalization ability of precipitation model prediction based on the nonlinear and non-stationary characteristics of precipitation data, this paper proposes a precipitation prediction model based on whale optimization Algorithm (WOA), Complete Ensemble Empirical Mode Decomposition (CEEMDAN), and Bidirectional Long Short Term Memory Network (BiLSTM). Compared to the default parameters of CEEMDAN, WOA is used to optimize the key parameters of CEEMDAN, decomposing precipitation data into several intrinsic mode functions (IMFs) to extract multi-scale feature information. Predict each IMF using the BiLSTM model and reconstruct the predicted results into the final precipitation forecast. This article takes the historical precipitation data of a city in Guangdong Province as an example to verify that the model has high accuracy and robustness in precipitation prediction.

关键词： Adaptation models Precipitation Accuracy Urban areas Predictive models White noise Prediction algorithms Feature extraction Data models whale optimization algorithms

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Fractional Order PID Control Applied to a Pasteurization Plant

Fractional Order PID Control Applied to a Pasteurization Pla...

引用

IEEE Biennial Congress of Argentina (ARGENCON)

作者： Luis Caiza Marco Herrera Noel Pérez-Pérez Fabricio Yépéz Diego S. Benítez Oscar Camacho Colegio de Ciencias e Ingenierí as Universidad San Francisco de Quito USFQ Quito Ecuador

ISBN: (数字)9798350365931

ISBN: (纸本)9798350365948

Milk pasteurization is complex and nonlinear, challenging to manage with traditional controllers such as ON-OFF or PID. This study examines fractional-order PID (FO-PID) control due to its ability to handle numerous variables effectively. The FO-PID controller ensures performance and robustness to maintain the required temperature limits. Using the Armfield Process Plant Trainer, PCT23MKII, a realistic small-scale model of a pasteurizing process is established. This system includes high-/low-level switches and two-way solenoid valves for tank filling operations. The results indicate that FO-PID extends the functionality of classical PID controllers by enhancing the delivery of the control signal.

关键词： Transmitters Process control Valves whale optimization algorithms Robustness Temperature control Solenoids Particle swarm optimization Tuning Testing

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Feature Selection Method Based On GWO-PSO for Coronary Artery Disease Classification

Feature Selection Method Based On GWO-PSO for Coronary Arter...

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Advances in Electrical, Computing, Communication and Sustainable Technologies (ICAECT), International Conference on

作者： Eluri Rama Krishna Nagaraju Devarakonda School of Computer Science & Engineering VIT-AP University Andhra Pradesh India

In this analysis, optimization of Hybrid Grey Wolf technique for Feature Selection analysis is implemented. In many areas standard performance is given by Grey Wolf Optimizer's (GWO). To enhance the performance different GWO factors are signified GWO mainly based on the two conflicting concepts. This will exploit the optimal solutions. The performance of search algorithms is improved by balancing the both exploration and exploitation. For continuous search space problems are obtained from the original hybrid approach which is superior to performance. The main binary problem is fromfeature selection. Hence hybrid PSOGWO is also known as BGWOPSO. This is the best feature subset. To produce the best results, Euclidean separation matrix and K-Nearest Neighbor's classifier are used. Performance is evaluated using one common benchmark dataset from the UCI repository. According to the findings, the whale optimization algorithm, binary genetic algorithm, binary PSO, binary genetic algorithm, and Binary GWO (BGWO) provide the highest levels of performance in terms of accuracy, the selection of the most effective optimal features, and the amount of time required to compute.

关键词： Support vector machines Sensitivity and specificity Feature extraction Search problems whale optimization algorithms Classification algorithms Particle swarm optimization

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Red Deer Algorithm-Based Optimal Total Harmonic Distortion Minimization for Multilevel Inverters

Red Deer Algorithm-Based Optimal Total Harmonic Distortion M...

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Renewable Energy and Hydrogen Technologies (GlobConHT), IEEE IAS Global Conference on

作者： Taha A. Taha Mohd Khair Hassan Noor Izzri Abdul Wahab Hussein I. Zaynal Department of Electrical and Electronics Engineering University Putra Malaysia (UPM) Selangor Malaysia Computer Engineering Technology Department Al-Kitab University Kirkuk Iraq

This study offers a new Red Deer Algorithm (RDA) optimization technique for total harmonic distortion (THD) minimization in multilevel inverters (MLIs). RDA belongs to the class of swarm-based biologically inspired optimization methods. To test the angles determined via RDA optimization, a single-phase seven-level cascade multi-level inverter with symmetrical DC sources was used in this study. The switching angles for the optimally minimized total harmonic distortion (OMTHD) were computed via RDA optimization. RDA optimization was compared to meta-heuristic algorithms like the Improved whale optimization Algorithm (IWOA), whale optimization Algorithm (WOA), Sunflower Optimizer (SFO), Particle Swarm optimization (PSO), Krill Herd (KH), Grey Wolf Optimizer (GWO), Galactic Swarm optimization (GSA), Genetic Algorithm (GA), Fruit Fly optimization Algorithm (FFO) and Artificial Greyctric Field Algorithm (AEFA). The RDA optimization outperformed the ten algorithms used as benchmark frameworks in this study as it can find angles with minimum THD for the modulation index in 0–1.

关键词： Total harmonic distortion Switches Benchmark testing Multilevel inverters Minimization whale optimization algorithms Particle swarm optimization

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