New Improved Fractional Order Differentiator Models Based on Optimized Digital Differentiators by Maneesha Gupta, Richa Yadav

“…Different evolutionary algorithms (EAs), namely, particle swarm optimization (PSO), genetic algorithm (GA), and PSO-GA hybrid optimization, have been used to optimize digital differential operators so that these can be better fitted to exemplify their new improved fractional order differentiator counterparts. …”
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Weakly supervised semantic segmentation and optimization algorithm based on multi-scale feature model by Changzhen XIONG, Hui ZHI

“…In order to improve the accuracy of weakly-supervised semantic segmentation method,a segmentation and optimization algorithm that combines multi-scale feature was proposed.The new algorithm firstly constructs a multi-scale feature model based on transfer learning algorithm.In addition,a new classifier was introduced for category prediction to reduce the failure of segmentation due to the prediction of target class information errors.Then the designed multi-scale model was fused with the original transfer learning model by different weights to enhance the generalization performance of the model.Finally,the predictions class credibility was added to adjust the credibility of the corresponding class of pixels in the segmentation map,avoiding false positive segmentation regions.The proposed algorithm was tested on the challenging VOC 2012 dataset,the mean intersection-over-union is 58.8% on validation dataset and 57.5% on test dataset.It outperforms the original transfer-learning algorithm by 12.9% and 12.3%.And it performs favorably against other segmentation methods using weakly-supervised information based on category labels as well.…”
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Resilient VPP cost optimization in DER-driven microgrids for large distribution systems considering uncertainty during extreme events by T.D. Suresh, M. Thirumalai, R. Hemalatha, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

“…Utilizing a modified IEEE 118-bus radial distribution system (RDS), segmented into residential, commercial, and industrial zones, the black widow optimization (BWO) algorithm is employed to optimally size and site VPPs, minimizing operational costs and maximizing system resilience. …”
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An Effective GTO Algorithm-Based Cost-Benefit Analysis of DISCOs by Optimal Allocation of DG and DSTATCOM in a Radial Distribution Network by RAM PRASAD KANNEMADUGU, V. Adhimoorthy, A. Lakshmi Devi

“…This paper maximizes the cost–benefit, and voltage stability of DISCOs is improved by optimally considering the Distributed Generation (DGs) and DSTATCOM. …”
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An Adaptive Fusion Path Tracking Strategy for Autonomous Vehicles Based on Improved ACO Algorithm by Jihan Zhang, Yuan Wang, Jinyan Hu, Hongwu You

“…Although methods based on dynamic models and optimization theory can improve tracking performance, most autonomous systems lack high-fidelity models and the complexity of optimization processes lead to increase computational burden. …”
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Adaptive Bayesian optimization for proportional derivative control in double-acting piston pump ventilators by Cong Toai Truong, Trung Dat Phan, Van Tu Duong, Huy Hung Nguyen, Thanh Truong Nguyen, Tan Tien Nguyen

“…Experimental results demonstrate that the proposed algorithm significantly improves system performance, reducing both tidal volume error and control cost compared to manual tuning. …”
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REVIEW OF FEATURE SELECTION METHODS USING OPTIMIZATION ALGORITHM (Review paper for optimization algorithm) by Zana O. Hamad

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Spatial Position Optimization of Components in the Labeling Robot System for Bundled Bars by Zhang Fuxiang, Zheng Yu, Huang Yongjian, Wang Chunmei, Huang Fengshan

“…Taking the shortest total stroke of the robot labeling process as the optimization goal of the placement position of the industrial robot and label printer, an improved particle swarm optimization algorithm is used for optimization calculation to obtain the optimal spatial position of the industrial robot and label printer, which improves the work efficiency of the labeling robot system, and has guiding significance for the practical application of the system.…”
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Heuristically enhanced multi-head attention based recurrent neural network for denial of wallet attacks detection on serverless computing environment by Sarah A. Alzakari, Mohammad Alamgeer, Abdullah M. Alashjaee, Monir Abdullah, Khalid Nazim Abdul Sattar, Asma Alshuhail, Ahmad A. Alzahrani, Abdulwhab Alkharashi

“…The detection and classification of DoW attacks, the multi-head attention-based bi-directional gated recurrent unit (MHA-BiGRU) model is utilized. Eventually, the improved secretary bird optimizer algorithm (ISBOA)-based hyperparameter choice process is accomplished to optimize the detection results of the MHA-BiGRU model. …”
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Optimized parameter estimation of lithium-ion batteries using an improved cuckoo search algorithm under variable temperature profile by Tasadeek Hassan Dar, Satyavir Singh

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Congestion Management Using an Optimized Deep Convolution Neural Network in Deregulated Environment by Dhanadeepika B., Vanithasri M., Chakravarthi M.

“…The most important results for the test system indicating convergence profile, congestion cost, and change in real-power and voltage magnitude are obtained by the simulation in MATLAB, and on the basis of the obtained simulation outcomes, it is evident that the proposed Improved Lion Algorithm optimized Deep Convolution Neural Network displays phenomenal computation performance in minimizing congestion losses at minimum congestion costs. …”
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Optimization of New Energy Vehicle Industry Structure Based on Optimization Link Prediction Similarity Algorithm and CGE by Zhenjun Xie

“…In light of the growing global concerns over energy and climate change, new energy vehicles are confronted with both opportunities and challenges posed by industrial structural transformation. To foster the optimization of the new energy vehicle industry structure while considering environmental impact, this paper first uses an improved link prediction algorithm to construct an industrial structure optimization model. …”
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Improving heat exchanger fouling detection for phosphoric acid concentration units: A hybrid inverse approach integrating genetic algorithms and the Levenberg-Marquardt technique by Ridha Zitouni, Ali Fguiri, Amine Aymen Assadi, Mohammod Hafizur Rahman, Abdetif Amrane, Juan Pedro Solano, Mohamed-Razak Jeday

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A hybrid machine learning algorithm approach to predictive maintenance tasks: A comparison with machine learning algorithms by Jorge Paredes, Danilo Chávez, Ramiro Isa-Jara, Diego Vargas

“…However, there is room for improvement in this prediction. In this paper, a hybrid approach that combines supervised learning (multi-layer perceptron MLP) and reinforcement learning (Q-learning) algorithms is proposed with the aim of improving the accuracy and precision of predicting the RUL. …”
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Credit card fraud Detection using Feature select method and improved machine learning algorithm by Mohammed AL-Hammadi

“…The SVM classification model then performs the final classification, with its hyperparameters optimized through the particle swarm optimization (PSO) technique. …”
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Air Quality Prediction Using Neural Networks with Improved Particle Swarm Optimization by Juxiang Zhu, Zhaoliang Zhang, Wei Gu, Chen Zhang, Jinghua Xu, Peng Li

“…To address this challenge, we propose a novel prediction model that integrates an adaptive-weight particle swarm optimization (AWPSO) algorithm with a back propagation neural network (BPNN). …”
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Multi-Project Staff Scheduling Optimization Considering Employee Welfare in Construction Projects by Junlong Peng, Fei Zhou

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Using multiple machine learning algorithms to optimize the water quality index model and their applicability by Fei Ding, Shilong Hao, Wenjie Zhang, Mingcen Jiang, Liangyao Chen, Haobin Yuan, Nan Wang, Wenpan Li, Xin Xie

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Improving kernel ridge regression for medical data classification based on meta-heuristic algorithms

“…The development of meta-heuristic algorithms has helped in solving difficult issues. In this paper, the main improvement is included in the pelican optimization algorithm by applying elite opposite-based learning (EOBL) to improve population diversity in the search space for selecting the best hyperparameters. …”
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Integrating Machine Learning Algorithms: A Hybrid Model for Lung Cancer Outcome Improvement by Pradnyawant M. Gote, Praveen Kumar, Hemant Kumar, Prateek Verma, Moses Makuei Jiet

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