Optimizing CNN-Based Diagnosis of Knee Osteoarthritis: Enhancing Model Accuracy with CleanLab Relabeling by Thomures Momenpour, Arafat Abu Mallouh

Get full text

A fuzzy-optimized multi-level random forest (FOMRF) model for the classification of the impact of technostress by Gabriel James, Ifeoma, David, John, Samuel, Enefiok, Imeh Umoren, Ubong Etuk, Aloysius, Anietie, Saviour, Chikodili

“…To address this, this study proposes a Fuzzy-Optimized Multi-Level Random Forest (FOMRF) model that integrates fuzzy logic with machine learning to enhance classification accuracy and interpretability. …”
Get full text

Prediction of Gasification Process via Random Forest Regression Model Optimized with Meta-Heuristic Algorithms by Eunsung Oh

Get full text

An adaptive Home Energy Management system for prosumers in peer-to-peer trading networks with machine learning optimization by Ameni Boumaiza, Kenza Maher

Subjects: Get full text

Forecasting and Comparative Application of PV System Electricity Generation for Sprinkler Irrigation Machines Based on Multiple Models by Bohan Li, Kenan Liu, Yaohui Cai, Wei Sun, Quan Feng

Subjects: Get full text

A novel hybrid extreme learning machine-based diagnosis model for sensor node faults in aquaculture by Bing Shi, Zelin Gao, Tianheng Pu, Jianming Jiang, Yueping Sun

“…Additionally, parameters such as $$\sigma ,\textrm{n} ,d,\gamma$$ in the hybrid kernel function, and the penalty coefficient C, were also optimized to improve classification accuracy. A diagnosis model of a hybrid extreme learning machine based on an updated particle swarm optimization for sensor node faults was developed. …”
Get full text

Dissolved Oxygen Prediction Based on SOA-SVM and SOA-BP Models by ZHANG Xuekun

“…To improve the accuracy of dissolved oxygen prediction,this paper researches and proposes a prediction method that combines seagull optimization algorithm (SOA) with support vector machine (SVM) and BP neural network,prepares four prediction schemes based on the monthly dissolved oxygen monitoring data of the Jinghong Power Station in Xishuangbanna,a national important water supply source in Yunnan Province,from January 2009 to September 2020,optimizes the key parameters of SVM and weight threshold of BP neural network by SOA to construct SOA-SVM and SOA-BP models,predicts the dissolved oxygen of Jinghong Power Station based on the models,and compares the prediction results with those of SVM and BP models.The results show that:The absolute values of the average relative errors of the SOA-SVM and SOA-BP models for the 4 schemes of dissolved oxygen prediction are between 4.07%~4.98% and 3.85%~4.83%,and that of the average absolute errors are 0.309~0.374 mg/L and 0.294~0.371 mg/L,respectively.With better prediction accuracy than SVM and BP models,they have good prediction accuracy and generalization ability.SOA can effectively optimize the key parameters of SVM and weight threshold of BP neural network.SOA-SVM and SOA-BP models are feasible for dissolved oxygen prediction,which can provide references for related prediction research.…”
Get full text

Febrile disease modeling and diagnosis system for optimizing medical decisions in resource-scarce settings by Daniel Asuquo, Kingsley Attai, Okure Obot, Moses Ekpenyong, Christie Akwaowo, Kiirya Arnold, Faith-Michael Uzoka

Get full text

The Model for Supporting Decision-Making During Designing Programs of Innovation Development at Enterprises of Electro-Technical Industry of Machine-Building by V. G. Anisimov, E. G. Anisimov, A. Ya. Chernysh, D. A. Melnik

“…Cost minimization is a criterion of decision optimality in the model. One specific feature of the model is taking into account the uncertainty in estimation of possible costs connected with development and implementation of projects, included in the program. …”
Get full text

An effectiveness of machine learning models for estimate the financial cost of assistive services to disability care in the Kingdom of Saudi Arabia by Obaid Algahtani, Mohammed M. A. Almazah, Farouq Alshormani

“…Eventually, the modified pelican optimization algorithm (MPOA) is utilized to fine-tune the optimal hyperparameter of ensemble model parameters to achieve high predictive performance. …”
Get full text

Optimized Ensemble Methods for Classifying Imbalanced Water Quality Index Data by Zaharaddeen Karami Lawal, Ali Aldrees, Hayati Yassin, Salisu Dan'azumi, Sujay Raghavendra Naganna, Sani I. Abba, Saad Sh. Sammen

“…This study aimed to develop an effective ensemble model for classifying river water as drinkable or polluted using advanced machine learning. …”
Get full text

Data-Driven Optimization Method for Recurrent Neural Network Algorithm: Greenhouse Internal Temperature Prediction Model by Kwang Cheol Oh, Sunyong Park, Seok Jun Kim, La Hoon Cho, Chung Geon Lee, Dae Hyun Kim

“…We developed an internal environment prediction model for smart greenhouses using machine learning models. …”
Get full text

AI enhanced model predictive control for optimizing LPG recovery through integrated computational modeling design of experiments and multivariate regression by Basma Abd El Hakim, Mahmoud Abdel-Halim Abdel-Goad, M. E. Awad, Abeer M. Shoaib

Get full text

Designing Predictive Analytics Frameworks for Supply Chain Quality Management: A Machine Learning Approach to Defect Rate Optimization by Zainab Nadhim Jawad, Balázs Villányi

Get full text

Optimizing agricultural yield: a predictive model for profitable crop harvesting based on market dynamics by Nilesh P. Sable, Nilesh P. Sable, Vinod Kumar Shukla, Parikshit N. Mahalle, Vijayshri Khedkar

“…This research introduces a novel forecasting model that forecasts the most profitable months to harvest different crops, to optimize agricultural productivity. …”
Get full text

Prediction of failures in the project management knowledge areas using optimized ensemble models in software companies by Lamia Berriche, Abderrazak Loulizi

“…Our optimized classical machine learning models’ accuracies outperformed state-of-the-art techniques. …”
Get full text

Fine-tuning optimization of poly lactic acid impact strength with variation of plasticizer using simple supervised machine learning methods by Jaka Fajar Fatriansyah, Elvi Kustiyah, Siti Norasmah Surip, Andreas Federico, Agrin Febrian Pradana, Aniek Sri Handayani, Mariatti Jaafar, Donanta Dhaneswara

Get full text

Optimization and Decision-Making for a Service Contract on Machine Maintenance by Zeyu Luo, Zhixin Yang, Jinbiao Wu, Zhaotong Lian

“…We investigate a novel maintenance service contract model. The service provider of the machine must determine the optimal pricing structure and staffing levels, while the client selects an appropriate plan for the warranty duration. …”
Get full text

Optimization Strategies in Quantum Machine Learning: A Performance Analysis by Nouf Ali AL Ajmi, Muhammad Shoaib

“…These results underscore the critical role played by optimizer selection in enhancing model performance and efficiency in quantum machine learning applications, offering valuable insights for practitioners in the field.…”
Get full text

Optimize building energy efficiency design and evaluation with machine learning by Chun Gu

“…With the increasing demand for energy efficiency optimization in the building industry, this study explores the application of machine learning technology in building energy efficiency design and evaluation. …”
Get full text