Optimizing precision farming: enhancing machine learning efficiency with robust regression techniques in high-dimensional data by Nour Hamad Abu Afouna, Majid Khan Majahar Ali

“…As a result of the study, the best models are the Ridge model with the MM bisquares before heterogeneity, the Ridge model with the MM method after heterogeneity, and the Lasso model with the MM method before heterogeneity and the Lasso model with MM Hampel after heterogeneity. …”
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Weight optimization of steel lattice transmission towers based on Differential Evolution and machine learning classification technique by Tran-Hieu Nguyen, Anh-Tuan Vu

“…This paper presents a method that integrates Differential Evolution (DE), a powerful optimization algorithm, and a machine learning classification model to minimize the weight of steel lattice towers. …”
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STRUCTURE ANALYSIS AND MULTI-OBJECTIVE OPTIMIZATION DESIGN OF A DEWATERING BUCKET FOR A PULSATOR WASHING MACHINE by CAI Yun, PENG Liang, LIU Xue, CHENG ZhiWen

“…In order to suppress the vibration noise of a tumble dryer（ internal barrel） in a pulsator washing machine,and to optimize the internal barrel for better performance,firstly,a parameterized finite element model of the internal barrel was established by Solidworks software and imported into ANSYS Workbench software. …”
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Oil well productivity capacity prediction based on support vector machine optimized by improved whale algorithm by Kuiqian Ma, Chunxin Wu, Yige Huang, Pengfei Mu, Peng Shi

“…The degree of each factor influence on oil well productivity capacity was analyzed by using the mean decrease impurity (MDI) method, the feature parameters were sequentially excluded, and redundant features that do not affect the prediction accuracy of the model were removed. And then support vector machine (SVM) optimized by improved whale optimization algorithm (IWOA) was used to establish prediction model for oil well productivity capacity. …”
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Enhancing CO2 emissions prediction for electric vehicles using Greylag Goose Optimization and machine learning by Ahmed El-Sayed Saqr, Mohamed S. Saraya, El-Sayed M. El-Kenawy

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Electric load forecasting based on kernel extreme learning machine optimized by improved sparrow search algorithm by Diming Zhang, Yuchen Xu, Yuanjiang Li

“…These subsequences are then integrated with the Kernel Extreme Learning Machine (KELM) to develop a forecasting model named WHFSSA-KELM. …”
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Optimizing the early diagnosis of neurological disorders through the application of machine learning for predictive analytics in medical imaging by Vijaya Bhaskar Sadu, Sathvik Bagam, Mohd Naved, Siva Krishna Reddy Andluru, Kamalakar Ramineni, Meshal Ghalib Alharbi, Sudhakar Sengan, Rahmaan Khadhar Moideen

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Optimizing Boride Coating Thickness on Steel Surfaces Through Machine Learning: Development, Validation, and Experimental Insights by Selim Demirci, Durmuş Özkan Şahin, Sercan Demirci, Armağan Gümüş, Mehmet Masum Tünçay

“…In this study, a comprehensive machine learning (ML) model was developed to predict and optimize boride coating thickness on steel surfaces based on boriding parameters such as temperature, time, boriding media, method, and alloy composition. …”
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Optimizing radiomics for prostate cancer diagnosis: feature selection strategies, machine learning classifiers, and MRI sequences by Eugenia Mylona, Dimitrios I. Zaridis, Charalampos Ν. Kalantzopoulos, Nikolaos S. Tachos, Daniele Regge, Nikolaos Papanikolaou, Manolis Tsiknakis, Kostas Marias, ProCAncer-I Consortium, Dimitrios I. Fotiadis

“…Abstract Objectives Radiomics-based analyses encompass multiple steps, leading to ambiguity regarding the optimal approaches for enhancing model performance. …”
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A combined improved dung beetle optimization and extreme learning machine framework for precise SOC estimation by Kaihua Yao, Xinyu Yan, Xiling Mao, Mengwei Li, Xiao Li, Ziyu Lian, Yuxiang Han

“…In this work, we propose a combined Improved Dung Beetle Optimization (IDBO) and Extreme Learning Machine (ELM) framework for SOC estimation and evaluate the efficiency of the BMS. …”
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Mutual-Energy Inner Product Optimization Method for Constructing Feature Coordinates and Image Classification in Machine Learning by Yuanxiu Wang

“…And then, a mutual-energy inner product optimization model is built to extract the data features, and the convexity and concavity properties of its objective function are discussed. …”
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Machine Learning-Driven Structural Optimization of a Bistable RF MEMS Switch for Enhanced RF Performance by J. Joslin Percy, S. Kanthamani, S. Mohamed Mansoor Roomi

“…The proposed I-clamp switch was optimized using an eXtreme Gradient Boost (XGBoost) ML model to predict optimal design parameters while significantly reducing the computational overhead of conventional EM simulations. …”
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Effect of the Sampling of a Dataset in the Hyperparameter Optimization Phase over the Efficiency of a Machine Learning Algorithm by Noemí DeCastro-García, Ángel Luis Muñoz Castañeda, David Escudero García, Miguel V. Carriegos

“…Selecting the best configuration of hyperparameter values for a Machine Learning model yields directly in the performance of the model on the dataset. …”
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Multi-objective portfolio optimization using real coded genetic algorithm based support vector machines by B. Surja, L. Chin, F. Kusnadi

“…Classifying stocks help investors build portfolios that align with their risk profiles and investment goals, in which the model was constructed using the one-versus-one support vector machines method with a radial basis function kernel. …”
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Data-Driven Optimization of Aspect Ratio in Permanent Magnet Machines Using Deep Learning and SHAP Analysis by Kyeong Jin Kim, Ji Hoon Park, Dong Hoo Min, Seun Guy Min

“…The aspect ratio, defined as the ratio of the outer diameter to the stack length, is a critical parameter in permanent magnet (PM) machine design, with a profound impact on motor performance. …”
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Machine Learning-driven Identification of the Honeymoon Phase in Pediatric Type 1 Diabetes and Optimizing Insulin Management by Satheeskumar R.

“…The aim was to develop and validate a machine learning (ML)-driven method for accurately detecting this phase to optimize insulin therapy and prevent adverse outcomes. …”
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Optimization of urban green space in Wuhan based on machine learning algorithm from the perspective of healthy city by Xuechun Zhou, Xiaofei Zou, Wenzuixiong Xiong

“…Adopting a healthy city development perspective, the research aims to assess the impact of green space optimization on urban health, economic performance, and social structure.MethodsA multivariable model was constructed using random forest and Support Vector Machine (SVM) algorithms to evaluate the influence of key indicators on urban green space. …”
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OPTIMIZING THE PLACEMENT OF A BATCH OF WORK-PIECES AT A MULTI-POSITION ROTARY TABLE OF TRANSFER MACHINE by N. N. Guschinsky, B. M. Rozin

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Enhanced data-driven shear strength predictive modeling framework for RCDBs using explainable boosting-based ensemble learning algorithms coupled with Bayesian optimization by Imad Shakir Abbood, Noorhazlinda Abd Rahman, B.H. Abu Bakar

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Stochastic Modeling and Analysis with Energy Optimization for Wireless Sensor Networks by DongHong Xu, Ke Wang

“…Due to the battery limitation of wireless sensor network (WSN), there is imperative requirement of energy saving and optimization in practical application of WSN. In order to optimize the energy of WSN, in this paper, a stochastic energy model for WSN is proposed. …”
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