A novel multi-task learning model based on Transformer-LSTM for wind power forecasting by Rongquan Zhang, Siqi Bu, Yuxia Zheng, Gangqiang Li, Xiupeng Wan, Qiangqiang Zeng, Min Zhou

“…Finally, to improve the prediction accurateness, a new heuristic algorithm, namely hybrid Cauchy mutation-based Elk herd and sand cat swarm optimization, is proposed to optimize the model hyperparameters. …”
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Application of Artificial Intelligence Computer Intelligent Heuristic Search Algorithm by Fanghai Gong

“…After 231 iterations of particle swarm optimization algorithm, the optimal value is 6.83650785e-001. …”
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Machine learning driven diabetes care using predictive-prescriptive analytics for personalized medication prescription by Manaf Zargoush, Somayeh Ghazalbash, Mahsa Madani Hosseini, Farrokh Alemi, Dan Perri

“…Effective and personalized treatment strategies are essential for improving patient outcomes and reducing healthcare costs. …”
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Blind equalization algorithm based on complex support vector regression by Ling YANG, Liang CHEN, Bin ZHAO, Guolong ZHANG, Yuan LI

“…A new blind equalization algorithm for complex valued signals was proposed based on the framework of complex support vector regression(CSVR).In the proposed algorithm,the error function of multi-modulus algorithm (MMA) was substituted into CSVR to construct the cost function,and the regression relationship was established by widely linear estimation,and the equalizer coefficients were determined by the iterative re-weighted least square (IRWLS) method.Different from spliting the complex valued signals into real valued signals used in support vector regression,the Wirtinger’s calculus was used in complex support vector regression to analyze the complex signals directly in the complex regenerative kernel Hilbert space.Simulation experiments show that for QPSK modulated signals,compared with the blind equalization algorithm based on support vector regression,the equalization performance of the proposed algorithm is significantly improved in linear channel and nonlinear channel by choosing appropriate kernel function and iterative optimization method.…”
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Interior Point Algorithm for Multi-UAVs Formation Autonomous Reconfiguration by Wang Jian-hong, Rana Javed Masood

“…Combined with three kinds of cost functions, nonlinear dynamic equations, and four inequality constraints, one nonlinear multiobjective optimization problem is constructed. …”
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Time-Dependent Vehicle Routing Problem with Drones Under Vehicle Restricted Zones and No-Fly Zones by Shuo Wei, Houming Fan, Xiaoxue Ren, Xiaolong Diao

“…Compared to the genetic neighborhood search algorithm and the hybrid genetic algorithm, the improvement rates are 5.1% and 13.0%, respectively. …”
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Optimal Design of Integrating Two‐Level Artificial Intelligent With Three Degrees of Freedom‐PDF (TLNF‐3DOFPDF) Controller for AGC of Three‐Area Multi‐Sources Power System... by Getaneh Mesfin Meseret, Rajesh Kumhar, Tarkesh Kumar Mahato, Nishant Kumar, Poonam Lakra, M. D. Mofeed Alam

“…Controller parameters are fine‐tuned using a novel metaheuristic method called the Skill Optimization Algorithm (SOA). The research assesses controller performance using multiple indices Integral of Time‐weighted Squared Error (ITSE), Integral of Squared Error (ISE), Integral of Time‐weighted Absolute Error (ITAE), and Integral of Absolute Error (IAE) and finds that ISE yields the most optimal results. …”
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Application of Improved Image Processing Technology in New Media Short Video Quality Improvement in Film and Television Postproduction by Yi Wang

“…In this paper, a convolutional neural network combined with a nonlinear activation function is used to establish an improved image processing technology model to efficiently extract image features. …”
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An Intelligent Client Selection Algorithm of Federated Learning for Class-imbalance by ZHU Suxia, WANG Yunmeng, YAN Peisen, SUN Guanglu

“… In the federated learning application scenario, if the data among the client devices shows the characteristics of non- independence identically distribution, or even class-imbalance, the optimization goal of the client local model will deviate from the global optimization goal, which brings great challenges to the performance of the global model. …”
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Launch dynamics modeling and simulation of box-type multiple launch rocket system considering plane clearance contact by Jinxin Tang, Guoping Wang, Genyang Wu, Yutian Sun, Lilin Gu, Xiaoting Rui

“…To quantify the contact force and friction effect between the slider and guide, the contact force model and modified Coulomb model were introduced. …”
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Investigation and application of data balancing and combined discriminant model in rock burst severity prediction by Shaohong Yan, Runze Liu, Yanbo Zhang, Xulong Yao, Yueqi Yang, Qi Wang, Bin Guo, Shuai Wang

“…Ultimately, a BO-MLP-RF composite prediction model was constructed based on Bayesian Optimization (BO), Multilayer Perceptron (MLP), and Random Forest (RF) algorithms, with the Bayesian Optimization method ensuring that the model fits the training data well and generalizes to the test data. …”
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Path Planning in Narrow Road Scenarios Based on Four-Layer Network Cost Structure Map by Ping Wang, Hao Zhang, Youming Tang

“…Second, an improved A* algorithm is employed for global planning to ensure safe navigation. …”
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Neurodynamic robust adaptive UWB localization algorithm with NLOS mitigation by Yanxu Liu, Enwen Hu, Yudong Chen, Changyou Guo

“…We proposed an adaptive distance error upper bound method to improve the accuracy of localization model. Tested in representative numerical simulation and real environments, our proposed robust adaptive positioning algorithm outperforms existing methods in terms of localization accuracy and robustness, especially in severe NLOS environments.…”
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NSGA-II-based load resource management for frequency and voltage support by Yaxin Wang, Zhihang Zhu, Zhihong Yu, Zigan Wang

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Combining Parallel Stochastic Methods and Mixed Termination Rules in Optimization by Vasileios Charilogis, Ioannis G. Tsoulos, Anna Maria Gianni

“…In this study, a combination of termination criteria is proposed, utilizing three different criteria to end the algorithmic process. These criteria include measuring the difference between optimal values in successive iterations, calculating the mean value of the cost function in each iteration, and the so-called “DoubleBox” criterion, which is based on the relative variance of the best value of the objective cost function over a specific number of iterations. …”
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Hybrid Adaptive Sheep Flock Optimization and Gradient Descent Optimization for Energy Management in a Grid-Connected Microgrid by Sri Harish Nandigam, Krishna Mohan Reddy Pothireddy, K. Nageswara Rao, Surender Reddy Salkuti

“…Results demonstrate the efficiency of the proposed hybrid algorithm, achieving substantial improvements in energy efficiency and cost reduction compared to traditional methods like interior point optimization, gradient descent, branch and bound, and a population-based algorithm named Golden Jackal optimization. …”
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A Global Path Planning Algorithm Based on Bidirectional SVGA by Taizhi Lv, Chunxia Zhao, Jiancheng Bao

“…This algorithm does not construct a visibility graph before the path optimization. …”
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Sorting misorganized books in libraries based on ant colony algorithm by Ling Chen

“…The global optimization possessed by ant colony algorithm can also make the convergence value of the model close to the optimal value, thereby improving the overall operational efficiency of the model. …”
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Cost-effectiveness analysis of best management practices for non-point source pollution in watersheds: A review by CHANG Jian, YU Jie, WANG Fei’er, ZHENG Siyuan

“…Application of cost-effectiveness analysis method included three categories, coupling NPS model with empirical calculation methods, coupling NPS model with economic model and cost-effectiveness analysis based on optimization algorithm. …”
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Water Quality Prediction Based on Hybrid Deep Learning Algorithm by Bhagavathi Perumal, Niveditha Rajarethinam, Anusuya Devi Velusamy, Venkatesa Prabhu Sundramurthy

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