Fine Tuning Hyperparameters of Deep Learning Models Using Metaheuristic Accelerated Particle Swarm Optimization Algorithm by Abdel-Hamid M. Emara, Ghada Atteia, Jawad Hasan Alkhateeb

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Enhanced genetic algorithm for indoor low-illumination stereo matching energy function optimization by Zhang Hongjin, Wei Hui

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Length Optimization of MEP Pipeline Integrated Modular Based on Genetic Algorithm by Xuefeng Zhao, Qiantai Yang, Gangwen Yan, Xiongtao Fan, Yinghui Yang, Huizhong Zhang, Song Chen

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Predicting Student Performance through Machine Learning Methods: Naive Bayesian Classifier by Chenyang Li, Qianzhi Zhou, Luming Du, Sihan Zhang

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Research and application of optimization of physical education training model based on multi-objective differential evolutionary algorithm by Man Wu

“…In order to study the application of the multi-objective differential evolution algorithm in the field of sports transportation. Based on the improvement of multi-objective differential evolution algorithm, this paper proposes the training model of PE education, and compares the prediction results and the actual results. …”
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Cultural Heritage Color Regeneration: Interactive Genetic Algorithm Optimization Based on Color Network and Harmony Models by Zhonghua Jiang, Qianlong Xia, Zhizhou Wang, Kaiwei Zhu, Qianyu Su, Jiajun Wang, Yirui Huang, Bo Wu, Yan Hong

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Early detection of monkeypox: Analysis and optimization of pretrained deep learning models using the Sparrow Search Algorithm by Amna Bamaqa, Waleed M. Bahgat, Yousry AbdulAzeem, Hossam Magdy Balaha, Mahmoud Badawy, Mostafa A. Elhosseini

“…The novelty lies in using SpaSA to optimize pre-trained CNNs' performance. The Xception model achieves 97.66% accuracy without optimization. …”
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Integrated Landslide Risk Assessment via a Landslide Susceptibility Model Based on Intelligent Optimization Algorithms by Xin Dai, Jianping Chen, Tianren Zhang, Chenli Xue

“…This study proposes an integrated landslide risk assessment via a landslide susceptibility model based on intelligent optimization algorithms. …”
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Emotion recognition with a Randomized CNN-multihead-attention hybrid model optimized by evolutionary intelligence algorithm by Syed Muhammad Salman Bukhari, Muhammad Hamza Zafar, Syed Kumayl Raza Moosavi, Filippo Sanfilippo

“…To address these challenges, we propose an innovative emotion recognition framework that integrates a Randomised Convolutional Neural Network (RCNN) with a Multi-Head Attention model, further optimized by the Football Team Training Algorithm (FTTA) metaheuristic to enhance network parameters effectively. …”
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Optimization Design of Multi-Blade Centrifugal Fan Based on Variable Weight PSO-BP Prediction Model and Multi-Objective Beluga Optimization Algorithm by Wenyang Jin, Jiaxuan Wang, Junyu Li, Ren Xu, Ming Zhou, Qibai Huang

“…This article proposes a prediction model and a multi-objective optimization algorithm and applies them to the optimization design of a multi-blade centrifugal fan. …”
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Web services composition algorithm based on the location of backup service and probabilistic QoS model by Hua WEN

“…For the service selection problem, an improved multiple objective optimization（MOO）algorithm was adopted to calculate the feasible solution set using clustering and QoS model. …”
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Web services composition algorithm based on the location of backup service and probabilistic QoS model by Hua WEN

“…For the service selection problem, an improved multiple objective optimization（MOO）algorithm was adopted to calculate the feasible solution set using clustering and QoS model. …”
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Rolling Bearing Fault Diagnosis Based on Optimized VMD Combining Signal Features and Improved CNN by Yingyong Zou, Xingkui Zhang, Wenzhuo Zhao, Tao Liu

“…The golden jackal optimization (GJO) algorithm is employed to optimize the key parameters of the VMD, enabling effective signal decomposition. …”
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Product perceptual design optimization model based on BP neural network by Lei Yong

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Optimization Models for Reducing the Air Pollutants Emission in the Production of Insulation Bituminous by Faezeh Borhani, Majid Shafiepour Motlagh, Amir Houshang Ehsani, Yousef Rashidi, Alireza Noorpoor, Saeid Maddah

“…For this purpose, first, the flow parameters of the chimney are measured with the KIMO gas analyzer, model KIGAS300, and then the pollutants Carbon monoxide, Hydrocarbons, and Nitrogen oxides are optimized of two methods in the MATLAB software using the Genetic Algorithm method and python software using the multiple regression with Sklearn and Statsmodels approach. …”
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A Model Predictive Control to Improve Grid Resilience by Joseph Young, David G. Wilson, Wayne Weaver, Rush D. Robinett

“…The following article details a model predictive control (MPC) to improve grid resilience when faced with variable generation resources. …”
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Study on optimization of Al6061 sphere surface roughness in diamond turning based on central composite design model and grey wolf optimizer algorithms by Le Thanh Binh, Duong Xuan Bien, Ngo Viet Hung, Chu Anh My, Hoang Nghia Duc, Nguyen Kim Hung, Bui Kim Hoa

“…This paper presents optimization results of the Al6061 surface roughness in turning ultra-precision based on the central composite design method (CCD) and the grey wolf optimization algorithm (GWO). …”
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Improved artificial bee colony algorithm for large scale colored bottleneck traveling salesman problem by Wenyong DONG, Xueshi DONG, Yufeng WANG

“…An improved artificial bee colony algorithm (IABC) was applied to solve the large scale CBTSP. …”
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Novel Gaussian-Decrement-Based Particle Swarm Optimization with Time-Varying Parameters for Economic Dispatch in Renewable-Integrated Microgrids by Yuan Wang, Wangjia Lu, Wenjun Du, Changyin Dong

“…Taking the economic cost of electricity consumption in the service area as the objective function and simultaneously meeting constraints such as power balance, power grid interactions, and energy storage systems, a microgrid economy dispatch model is constructed. An improved particle swarm optimization algorithm with time-varying parameters of the inertia weight and learning factor was designed to solve the optimal dispatching strategy. …”
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Aircraft range fuel prediction study based on WPD with IAPO optimized BiLSTM–KAN model by Weizhen Tang, Jie Dai, Yuantai Li

“…Ultimately, the multi-strategy improved APO is employed to optimize the hyperparameters of the BiLSTM–KAN model, allowing for the superposition of each subsequence to yield the final prediction results. …”
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