A Novel Approach for Evaluating Web Page Performance Based on Machine Learning Algorithms and Optimization Algorithms by Mohammad Ghattas, Antonio M. Mora, Suhail Odeh

“…By bridging the gap between predictive modeling and optimization, this study contributes valuable insights to practitioners and researchers alike, establishing new benchmarks for future investigations in web page performance evaluation.…”
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Trajectory Optimization of Packet Ferries in Opportunistic Social-Based Machine-to-Machine Networks by Xin Guan

“…We formulate the optimal issue into semi-Markov Decision Process model. …”
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Comparative Analysis of Machine Learning Models for CO Emission Prediction in Engine Performance by Beytullah Eren, İdris Cesur

“…This study presents a comparative analysis of machine learning models for predicting carbon monoxide (CO) emissions in automotive engines. …”
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Modeling of Battery Storage of Photovoltaic Power Plants Using Machine Learning Methods by Rad Stanev, Tanyo Tanev, Venizelos Efthymiou, Chrysanthos Charalambous

Subjects: “…battery energy storage system modeling…”
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A Digital Twin Framework With Meta- and Transfer Learning for Scalable Multi-Machine Modeling and Optimization in Semiconductor Manufacturing by Chin-Yi Lin, Tzu-Liang Tseng, Tsung-Han Tsai

“…Despite recent advances in Digital Twin (DT) technologies for semiconductor manufacturing, no existing research convincingly demonstrates a unified, rapidly scalable, and data-efficient DT framework that can effectively handle stringent multi-objective optimization under severe data scarcity. This absence of a comprehensive approach impedes widespread industry adoption, given the pressing need for flexible, universal solutions that rapidly adapt to diverse machines and processes. …”
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A Model for Detecting <i>Xanthomonas campestris</i> Using Machine Learning Techniques Enhanced by Optimization Algorithms by Daniel-David Leal-Lara, Julio Barón-Velandia, Lina-María Molina-Parra, Ana-Carolina Cabrera-Blandón

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Integrating Sentinel-1 SAR and Machine Learning Models for Optimal Soil Moisture Sensor Placement at Catchment Scale by Yi Xie, Guotao Cui, Kaifeng Zheng, Guoping Tang

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A hybrid machine learning model with self-improved optimization algorithm for trust and privacy preservation in cloud environment by Himani Saini, Gopal Singh, Sandeep Dalal, Iyyappan Moorthi, Sultan Mesfer Aldossary, Nasratullah Nuristani, Arshad Hashmi

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Safety Status Prediction Model of Transmission Tower Based on Improved Coati Optimization-Based Support Vector Machine by Xinxi Gong, Yaozhong Zhu, Yanhai Wang, Enyang Li, Yuhao Zhang, Zilong Zhang

“…Subsequently, we employ the improved coati optimization algorithm (ICOA) to refine the penalty parameters and kernel function of the support vector machine (SVM), thereby developing the safety state prediction model for the transmission tower. …”
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Theoretical investigations on analysis and optimization of freeze drying of pharmaceutical powder using machine learning modeling of temperature distribution by Turki Al Hagbani, Jawaher Abdullah Alamoudi, Majed A. Bajaber, Huda Ibrahim Alsayed, Halah Jawad Al-fanhrawi

“…Model optimization is achieved through the Fireworks Algorithm (FWA). …”
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Analysis and Optimization of Customer Lifetime Value Prediction using Machine Learning and Deep Learning Models by RFM Techniques by Leila Taherkhani, Amir Daneshvar, Hossein Amoozad Khalili, MohammadReza Sanaei

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Synergistic Framework for Fuel Cell Mass Transport Optimization: Coupling Reduced-Order Models with Machine Learning Surrogates by Shixin Li, Qingshan Liu, Yisong Chen

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Development of an Optimal Machine Learning Model to Predict CO₂ Emissions at the Building Demolition Stage by Gi-Wook Cha, Choon-Wook Park

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Optimizing machine learning for network inference through comparative analysis of model performance in synthetic and real-world networks by Ruby Khan, Sumbal Khan, Bakht Pari, Krzysztof Puszynski

“…These findings show that simpler machine learning models can outperform more sophisticated ones in some contexts, offering a more nuanced view of model selection based on network scale and complexity. …”
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Prediction of UHPC mechanical properties using optimized hybrid machine learning model with robust sensitivity and uncertainty analysis by ZhiGuang Zhou, Jagaran Chakma, Md Ahatasamul Hoque, Vaskar Chakma, Asif Ahmed

“…This study presents a comprehensive evaluation of three hybrid machine learning models XGB-LGB, RF-XGB, and ET-LGB for predicting the mechanical performance of Ultra-High-Performance Concrete (UHPC), including compressive strength (CS), flexural strength (FS), and tensile strength (TS). …”
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Prediction and Mapping of Soil Total Nitrogen Using GF-5 Image Based on Machine Learning Optimization Modeling by LIU Liqi, WEI Guangyuan, ZHOU Ping

“…Three distinct soil TN inversion models were constructed using these algorithms. To optimize model performance, ten-fold cross-validation was employed to determine the optimal parameters for each model. …”
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Particle Swarm Optimization of Support Vector Machine Inversion Model for Overhead Upright Piers Damage-Inducing Factor by Shiliang Zhou, Menghan Tang, Jun Wu, Chunru Ke

“…For intelligent monitoring of existing terminals, this research chooses Chongqing Xintian Port as the study object and proposes a support vector machine (SVM) damage-inducing factor (DIF) inversion model based on particle swarm optimization (PSO). …”
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Exploration of the optimal deep learning model for english-Japanese machine translation of medical device adverse event terminology by Ayako Yagahara, Masahito Uesugi, Hideto Yokoi

“…Objective The purpose of this study is to investigate the optimal machine translation model for the IMDRF-AET into Japanese for the part of a function for the automatic terminology mapping system. …”
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Machine learning models for predicting morphological traits and optimizing genotype and planting date in roselle (Hibiscus Sabdariffa L.) by Fazilat Fakhrzad, Warqaa Muhammed ShariffAl-Sheikh, Mohammed M. Mohammed, Heidar Meftahizadeh

“…In the present study, a machine learning framework was developed using Random Forest and Multi-layer Perceptron algorithms to model and predict key morphological traits, branch number, growth period, boll number, and seed number per plant, based on genotype and planting date. …”
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Machine learning-based optimal temperature management model for safety and quality control of perishable food supply chain by Joy Eze, Yanqing Duan, Elias Eze, Ramakrishnan Ramanathan, Tahmina Ajmal

“…The optimal storage temperature for a single perishable food is determined by applying the Pontryagin's maximum principle to solve the optimal control model problem. …”
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