Multipath Branch Model-Aided Differential Evolution Algorithm Based on Regional Error by Yang Liu, Yi-Xuan Zhang, Zhong-Chao Lin, Yu-Jia Zou

“…In order to overcome the defect of a single model in the adaptive antenna optimization problem and improving the efficiency and accuracy of the model, a method called multipath branching model-aided differential evolution algorithm analysis (MMDEA-RE) is proposed. …”
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An optimized informer model design for electric vehicle SOC prediction. by Xin Xie, Feng Huang, Yefeng Long, Youyuan Peng, Wenjuan Zhou

“…Therefore, based on the health assessment algorithm, a new optimized Informer model is proposed to predict SOC. …”
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Machine learning approach for optimizing usability of healthcare websites by Amandeep Kaur, Jaswinder Singh, Satinder Kaur

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A fast retrieval method for multilevel redundant data in grid resource business middle office based on improved decision tree algorithm by Wei Sun, Hui Liu, Yu Wang, Weihao Shi, Xiao Wang, Zhiwei Zou

“…The methodology first establishes a multi-level data decision tree using grid resource business middle-platform data, then applies a decision tree pruning algorithm based on Akaike information criterion. The ant colony algorithm optimizes the pruning parameters of the decision tree model, and after obtaining optimal pruning parameters, processes the grid resource business middle-platform data decision tree to generate an improved version. …”
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MULTI-OBJECTIVE OPTIMIZATION DESIGN OF ROADHEADER’S CUTTING HEAD BASED ON THE GA by ZHAO LiJuan, FAN JiaYi

“…In order to improve the dynamic reliability of the roadheader,the roadheader’s rigid-flexible coupled model was established based on virtual prototyp,dynamic reliability analysis was done on the rotary table of different structural parameters,evaluation function was established based on mechanical optimization design theory,the function’s design variables was half cone angle,helix Angle and cutting line spacing, the function’s objective function was the minimization of maximum equivalent stress as the objective function.The cutting head’s optimal structural parameters was obtained by genetic algorithm.Based on the cutting productivity and rotary table equivalent stress, the optimal yawing speed was obtained by optimized multi-objective.The results shows that after two optimizations,rotary table maximum stress is decreased 18.495 MPa,the fatigue life is improved from 3.067 E4 to 3.326 E6,productivity is improved 18.6 t/h,prediction error is less than 1.3%,meet the design requirement.This method provides data support for the structure and kinematic parameters of cutting head,provides a new method for the optimization design of heavy complicated mechanical equipment.…”
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Modelling and optimization of TPMLMs with slotted stators based on Bayesian DNN by Tao Wu, Peipei Dai, Kai Zhu, Yachao Zhu

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Detection of abnormal tourist behavior in scenic spots based on optimized Gaussian model for background modeling by Liu Xiaohua

“…The study proposed a background model constructed by an optimized Gaussian mixture model based on the background subtraction method to eliminate the background interference. …”
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The Optimal Cost Design of Reinforced Concrete Beams Using an Artificial Neural Network—The Effectiveness of Cost-Optimized Training Data by Jaemin So, Seungjae Lee, Jonghyeok Seong, Donwoo Lee

“…This study presents a method for the automated design of reinforced concrete (RC) beam cross-sections using an artificial neural network (ANN) trained with cost-optimized data generated by the crow search algorithm (CSA). …”
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Better care for children with appendicitis: implementation of antibiotic stewardship optimizes postoperative therapy by Beltz, Sebastian, Fischer, Stephanie, Huenger, Frank, Vahdad, Reza, Kalhoff, Hermann, Leutner, Andreas

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NVH Analysis and Optimization of Light Truck Electric Drive Axles Based on Romax by Hao Yingbo, Liu Lidong

“…In order to reduce the fluctuation of transmission error of the gear, the micro modification of the reducer gear was carried out by using genetic algorithm, thus the excitation of the electric drive axle caused by the gear meshing was reduced, and the NVH performance of the electric drive axle was further improved. …”
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Unconfined Compressive Strength Prediction of Rocks Using a Novel Hybrid Machine Learning Algorithm by Rafiqul Islam, Md. Arif Hossain

“…This paper introduces a novel methodology for predicting Unconfined Compressive Strength (UCS) in rocks by integrating Support Vector Regression (SVR) with two cutting-edge optimization algorithms: the Seahorse Optimizer (SO) and the COOT Optimization Algorithm (COOT). …”
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Optimization design and experiment of cam-elliptical gear combined vegetables curved surface labeling mechanism by Lei Zhang, Lei Zhang, Heng Zhou, Jianneng Chen, Jianneng Chen, Junhua Tong, Junhua Tong, Yang Liu, Xiaowei Zhang

“…In order to improve the motion performances of the cam-elliptical gear combined labeling mechanism and avoid labels damage, the NSGA-II algorithm is used to optimize the parameters of the mechanism, resulting in 80 sets of Pareto solutions. …”
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PCA-FSA-MLR Model and Its Application in Runoff Forecast by GUO Cunwen, CUI Dongwen

“…To improve the accuracy of runoff forecast,and establish a runoff forecast model combining principal component analysis (PCA),future search algorithm (FSA),and multiple linear regression (MLR),this paper reduces the dimensionality of the sample data by PCA,selects 8 standard test functions and simulates and verifies FSA under different dimensional conditions,optimizes MLR constant terms and partial regression coefficients by FSA,proposes a PCA-FSA-MLR runoff forecast model,constructs PCA-LS-MLR,PCA-FSA-SVM,and PCA-SVM models with dimensionality reduction processing by PCA and FSA-MLR,LS-MLR,FSA-SVM,and SVM without dimensionality reduction processing as a comparison model,and verifies each model through forecasting the annual runoff and monthly runoff in December of Longtan station in Yunnan Province.The results show that:①FSA has better optimization accuracy and global extremum search ability under different dimensional conditions;②The average absolute relative error of the annual runoff and monthly runoff in December of Longtan station through PCA-FSA-MLR model are 1.63% and 3.91% respectively,and its forecast accuracy is better than the other 7 models,with higher forecast accuracy and stronger generalization ability;③For the same model,the forecast accuracy after dimensionality reduction processing by PCA is better than that without dimensionality reduction processing,so the data dimensionality reduction by PCA is helpful to improve the forecast accuracy of models.…”
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Research on Stacking Distribution of Steel Plates Input Based on Improved Multi-objective Particle Swarm Optimization by ZHONG Chuanjie, CHENG Wenming, DU Run, GAO Xuchao, ZHANG Lin

“…Finally, the stacking situations before and after optimization were compared. Compared to the traditional stacking method used before optimization, the optimized stacking distribution scheme improved by 19.35%, 4.97%, and 62.23% under the three objectives, respectively, indicating a more significant optimization effect.ConclusionsBased on the actual demand of enterprises for optimizing automatic steel plate warehouse loading decisions, the PCDMOPSO algorithm has demonstrated good performance in the simulation test of solving the stack allocation model. …”
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Prediction of performance and emission features of diesel engine using alumina nanoparticles with neem oil biodiesel based on advanced ML algorithms by M. S. Aswathanrayan, N. Santhosh, Srikanth Holalu Venkataramana, Kurugundla Sunil Kumar, Sarfaraz Kamangar, Amir Ibrahim Ali Arabi, Sameer Algburi, Osamah J. Al-sareji, A. Bhowmik

“…Abstract The growing need for sustainable energy sources and stricter environmental regulations necessitate the development of alternative fuels with lower emissions and improved performance. This study addresses these challenges by optimizing the performance and emission characteristics of a single-cylinder diesel engine powered by neem oil biodiesel blends enhanced with alumina nanoparticlesusing the powerful desirability-based optimization. …”
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Optimization of Adversarial Reprogramming for Transfer Learning on Closed Box Models by Alexander Bott, Moritz Siems, Alexander Puchta, Jurgen Fleischer

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Cloud-based optimized deep learning framework for automated glaucoma detection using stationary wavelet transform and improved grey-wolf-optimization with ELM approach by Debendra Muduli, Syed Irfan Yaqoob, Santosh Kumar Sharma, Anuradha S. Kanade, Mohammad Shameem, Harendra S. Jangwan, P.M. Ashok Kumar, Abu Taha Zamani

“…Finally, an improved gray wolf optimization algorithm integrated with an extreme learning machine (IMGWO-ELM) classifies the images as either healthy or glaucomatous. …”
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Encapsulation of anticancer drugs into carbon nanotubes: Heuristic algorithm approach and mathematical model. by Kanes Sumetpipat, Duangkamon Baowan

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Construction of Graduate Behavior Dynamic Model Based on Dynamic Decision Tree Algorithm by Fen Yang

“…The results show that the big data integration system based on big data and dynamic decision tree algorithm has high adaptability. Incremental adaptive optimization of the traditional decision tree model can significantly improve the prediction effect and prediction time of dynamic data and provide theoretical support for the industrialization and social significance of big data technology. …”
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Integration of electric vehicle charging stations with distributed generation using multi-objective metaheuristic optimization by Aya Desoky Gaber, E.M. Abdallah, M.I. Elsayed, Ahmed Abdelbaset

“…This paper uses a multi-objective optimization approach metaheuristic algorithm, specifically the Whale Optimization Algorithm (WOA), Zebra Optimization Algorithm (ZOA), and Puma Optimization Algorithm (POA), to determine the optimal size and placement of DG units in the presence of EVCS. …”
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