Illustration Design Model with Clustering Optimization Genetic Algorithm by Jing Liu, Qixing Chen, Xiaoying Tian

“…This paper proposes an illustration art design model based on operator and clustering optimization genetic algorithm. …”
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Multi-objective Path Planning for AUVs Based on Improved Whale Optimization Algorithms and Fluid Disturbance Algorithms by Yuhong MA, Wen PANG, Daqi ZHU

“…To address the challenges of low path planning efficiency for autonomous undersea vehicle(AUV) in multi-target environments, as well as the limitations of the traditional whale optimization algorithm(WOA) in terms of susceptibility to local optima and inadequate adaptability to three-dimensional obstacle avoidance requirements, this study proposed a collaborative planning strategy that integrated a fluid perturbation algorithm with an improved WOA. …”
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A Bi-Level Capacity Optimization Method for Hybrid Energy Storage Systems Combining the IBWO and MVMD Algorithms by Qiaoqiao Xing, Shidong Li, Da Qiu, Yang Long, Qinyi Liao, Xiangjin Yin, Yunxiang Li, Kai Qian

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Robot Calibration Sampling Data Optimization Method Based on Improved Robot Observability Metrics and Binary Simulated Annealing Algorithm by Huakun Jia, Hanbo Zeng, Jiyan Zhang, Xiangyang Wang, Yang Lu, Liandong Yu

“…By utilizing the least squares method, the ideal pose transformation relationship between the robot’s base coordinate system and the laser tracker measurement coordinate system is derived, resulting in an error calibration model based on spatial single points. An improved robot observability metric combined with the Binary Simulated Annealing Algorithm (BSAA) is introduced to optimize the selection of calibration sampling data. …”
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An advanced CNN-attention model with IFTTA optimization for prediction air consumption of relay nozzles by Shen Min, Shao Ning, Cao Yongbo, Xiong Xiaoshuang, Yang Xuezheng, Wang Zhen, Yu Lianqing

“…This paper proposes a Convolutional Neural Network (CNN)-Attention regression model to predict air consumption of the relay nozzle, enhancing accuracy and efficiency with an Improved Football Team Training Algorithm (IFTTA). …”
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Optimization on Electric Construction Machinery Considering Time‐of‐Use Electricity Price Based on the Improved Crested Porcupine Optimizer Algorithm by Dawei Wang, Bo Gao, Lei Zhang

“…This paper introduces an innovative algorithm, the improved crested porcupine optimizer (ICPO), which incorporates Latin hypercube sampling for population initialization. …”
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Food sorting trajectory optimization based on improved NURBS and Delta parallel robots by CHEN Guangdong, SHAO Jian, WANG Feini, ZHAO Xuecheng

“…ObjectiveReduce the running time and impact of Delta robot in food sorting trajectory, improve the efficiency and stability of Delta robot operation.MethodsBased on the analysis of the food sorting system (using Delta robots), a Delta robot food sorting trajectory optimization method was proposed, which combined NURBS algorithm, sparrow search algorithm and butterfly optimization algorithm. …”
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Optimization of Offshore Wind and Wave Energy Co-Generation System Based on Improved Seagull Optimization Algorithm by Xiaoshi Zhuang, Honglue Wan, Dongran Song, Xinyu Fan, Yuchen Wang, Qian Huang, Jian Yang

“…Finally, a case study in the South China Sea validates the effectiveness of the model and algorithm. Using the improved algorithm, the optimal layout of the co-generation system and the optimal wind turbine parameters are obtained. …”
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Optimization of Body Size and Centroid Position of the Quadruped Robot based on Improved Particle Swarm Optimization Algorithm by Kai Tang, Huanlong Wu, Liang′an Zhang, Ranming Ji, Yongjie Zhao, Xiaoyi Wang, Xinjian Lu

“…Taking the quadruped robot as research object， a method to optimize body size and centroid position of the quadruped robot based on improved particle swarm optimization algorithm to enhance its stability is proposed. …”
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Advances in the Application of Intelligent Algorithms to the Optimization and Control of Hydrodynamic Noise: Improve Energy Efficiency and System Optimization by Maosen Xu, Bokai Fan, Renyong Lin, Rong Lin, Xian Wu, Shuihua Zheng, Yunqing Gu, Jiegang Mou

“…In recent years, intelligent algorithms represented by data-driven algorithms and heuristic algorithms have gradually emerged, showing great potential for development in hydrodynamic noise optimization applications. …”
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DESIGN OF AN IMPROVED MODEL FOR CARDIOVASCULAR DISEASE DETECTION USING DEEP CANONICAL CORRELATION ANALYSIS AND BIOINSPIRED OPTIMIZATION by Prakash Chandra Sahoo, Binod Kumar Pattanayak, Rajani Kanta Mohanty, Ayasa Kanta Mohanty

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A model for assessing lethal resistance levels of various buildings based on improved genetic algorithm + BP neural network optimization by Jie Zhang, Jie Zhang, Bin Tan, Bin Tan, Chaoxu Xia, Wenbin Yan, Yuan Tao, Yuan Tao, Ben Ma, Ben Ma

“…This study proposes a novel model that integrates an improved genetic algorithm (IGA) with an optimized backpropagation neural network (OBPNN) to address data imbalance in classifying building types for lethal resistance levels assessment. …”
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Bus Arrival Time Prediction Based on the Optimized Long Short-Term Memory Neural Network Model With the Improved Whale Algorithm by Bing Zhang, Lingfeng Tang, Dandan Zhou, Kexin Liu, Yunqiang Xue

“…Accurate prediction of bus arrival time is essential to achieve efficient bus dispatch and improve bus trip sharing rate. This article proposes using the improved whale optimization algorithm–long short-term memory (IWOA–LSTM) model to predict bus arrival times and improving the whale algorithm by optimizing the hyperparameters of the LSTM model, so that the advantages and disadvantages of the whale algorithm and the LSTM model can complement each other, thus enhancing the robustness of the model. …”
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A model adapted to predict blast vibration velocity at complex sites: An artificial neural network improved by the grasshopper optimization algorithm by Yong Fan, Guangdong Yang, Yong Pei, Xianze Cui, Bin Tian

“…Traditional empirical formulas often yield unsatisfactory prediction results. To improve the prediction accuracy of the peak particle velocity (PPV), this paper combines the ability of an artificial neural network (ANN) to solve complex nonlinear function approximations and the global optimization ability of 10 metaheuristic optimization algorithms and establishes an improved ANN prediction model. …”
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Research on Multi-Center Path Optimization for Emergency Events Based on an Improved Particle Swarm Optimization Algorithm by Zeyu Zou, Hui Zeng, Xiaodong Zheng, Junming Chen

“…Case studies were conducted to evaluate the feasibility and effectiveness of both the proposed model and the algorithm. Results indicate that the model accurately reflects the dynamics of emergency logistics operations, while the hybrid algorithm exhibits strong local optimization capabilities and robust performance in handling diverse and complex scenarios. …”
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Research on Optimization of Improved Gray Wolf Optimization-Extreme Learning Machine Algorithm in Vehicle Route Planning by Shijin Li, Fucai Wang

“…Extreme Learning Machine (ELM) algorithm model is introduced to accelerate Improved Gray Wolf Optimization (IGWO) optimization and improve convergence speed. …”
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Construction Scheduling Optimization of Prefabricated Buildings Under Resource Constraints Based on an Improved Whale Optimization Algorithm by Rui Su, Joey S. Aviles

“…To solve this model effectively, an Improved Whale Optimization Algorithm (IWOA) is developed, addressing the limitations of the standard WOA such as premature convergence and poor local search ability. …”
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Path Optimization Strategy for Unmanned Aerial Vehicles Based on Improved Black Winged Kite Optimization Algorithm by Shuxin Wang, Bingruo Xu, Yejun Zheng, Yinggao Yue, Mengji Xiong

“…The Black-winged Kite Optimization Algorithm (BKA) is likely to experience a sluggish convergence rate when confronted with the optimization of complex multimodal functions. …”
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Ballistic Fitting Impact Point Prediction Based on Improved Crayfish Optimization Algorithm by Baolu Yang, Liangming Wang, Jian Fu

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Parameter identification of photovoltaic inverter based on improved particle swarm optimization algorithm by LUO Jian, SUN Yue, JIANG Lijuan

“…The advantages of the proposed method can be obtained by comparing the synchronous identification results of the parameters， and the identification results were substituted into the simulation model.ResultsThe error of synchronous identification results of low sensitivity parameters was far beyond the acceptable range， and the error of relevant parameters identified by CGAPSO step by step was less than 1.1%， which was much higher than the accuracy of synchronous identification results.ConclusionsThe output data of the identification model based on the improved particle swarm optimization algorithm had a high agreement with the actual inverter working data，which could accurately reflect the actual working characteristics of the inverter.…”
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