Enhancing heart disease prediction accuracy by comparing classification models employing varied feature selection techniques by Balliu Lorena, Zanaj Blerina, Basha Gledis, Zanaj Elma, Meçe Elinda Kajo

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Construction cost prediction model for agricultural water conservancy engineering based on BIM and neural network by Kun Han, Tieliang Wang, Wenhe Liu, Chunsheng Li, Xiaochen Xian, Yingying Yang

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Multi-parameter optimization of layered WS2-polymer nanocomposite under mechanical loading by Elisaveta Kirilova, Tatyana Petrova, Boyan Boaydjiev, Rayka Vladova, Apostol Apostolov, Petia Dineva-Vladikova, Alexander Moravski

“… The aim of the study is to determine the optimal geometry and magnitude of the applied load to ensure safety and prevent delamination in a three-layered nanocomposite structure under axial mechanical loading. …”
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A Bidding Strategy for Power Suppliers Based on Multi-Agent Reinforcement Learning in Carbon–Electricity–Coal Coupling Market by Zhiwei Liao, Chengjin Li, Xiang Zhang, Qiyun Hu, Bowen Wang

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Comparison of Different Heuristics Integrated with Neural Networks: A Case Study for Earthquake Damage Estimation by Ayşe Berika Varol Malkoçoğlu, Zeynep Orman, Rüya Şamlı

“…In this study, various Machine Learning (ML) algorithms were compared on a public dataset of earthquakes, which had occurred worldwide and had a local magnitude Ml ≥ 3, and the algorithm with the highest performance was selected and optimized with various other algorithms. …”
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Revolutionizing Prenatal Care: Harnessing Machine Learning for Gestational Diabetes Anticipation by Sanmugasundaram Ravichandran, Hui-Kai Su, Wen-Kai Kuo, Manikandan Mahalingam, Kanimozhi Janarthanan, Bruhathi Sathyanarayanan, Kabilan Saravanan

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Day-Ahead Scheduling for Economic Dispatch of Combined Heat and Power With Uncertain Demand Response by Seyyed Ebrahim Hosseini, Mojtaba Najafi, Ali Akhavein, Mahdi Shahparasti

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Proposed improvement of product support packaging material defects using the Cross-Industry Standard Process for Data Mining (CRISP-DM) approach by Rina Fitriana, Anik Nur Habyba, Gina Almas Nabiha, Sannia Mareta

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Histopathological image based breast cancer diagnosis using deep learning and bio inspired optimization by Venkata Nagaraju Thatha, M. Ganesh Karthik, Venu Gopal Gaddam, D. Pramodh Krishna, S. Venkataramana, Kranthi Kumar Lella, Udayaraju Pamula

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Tactical Helicopter Transportation Planning for Offshore Personnel on the Norwegian Continental Shelf by Irina Gribkovskaia, Gaute Øiestad Slettemark

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Can Synthetic Data Allow for Smaller Sample Sizes in Chronic Urticaria Research? by Annika Gutsche, Pascale Salameh, Samad S. Jahandideh, Mehran Roodsaz, Serkan Kutan, Ali Salehzadeh‐Yazdi, Emek Kocatürk, Stamatios Gregoriou, Simon F. Thomsen, Kanokvalai Kulthanan, Papapit Tuchinda, Joachim Dissemond, Alicja Kasperska‐Zajac, Magdalena Zajac, Mateusz Zamłyński, Martijn vanDoorn, Claudio A. S. Parisi, Jonny G. Peter, Cascia Day, Cathryn McDougall, Michael Makris, Daria Fomina, Elena Kovalkova, Nikolai Streliaev, Gerelma Andrenova, Marina Lebedkina, Maryam Khoskhkui, Mehraneh M. Aliabadi, Andrea Bauer, Lea Kiefer, Melba Muñoz, Karsten Weller, Pavel Kolkhir, Martin Metz

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Artificial-Intelligence-Based Energy Management Strategies for Hybrid Electric Vehicles: A Comprehensive Review by Bin Huang, Wenbin Yu, Minrui Ma, Xiaoxu Wei, Guangya Wang

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Optimized ensemble learning for non-destructive avocado ripeness classification by Panudech Tipauksorn, Prasert Luekhong, Minoru Okada, Jutturit Thongpron, Chokemongkol Nadee, Krisda Yingkayun

“…Four algorithms were used to optimize the model weight distribution: Bayesian Optimisation, Differential Evolution, Particle Swarm Optimisation, and Grid Search. …”
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Optimized ANN Model for Predicting Buckling Strength of Metallic Aerospace Panels Under Compressive Loading by Shahrukh Khan, Saiaf Bin Rayhan, Md Mazedur Rahman, Jakiya Sultana, Gyula Varga

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Enhanced AdaBoostM1 with Multilayer Perceptron for Stock Price Prediction by Rebwar Mala Nabi, Soran AB. Saeed, Habibollah Haron

“…Among the predictive models, various adaptations of the AdaBoostM1 algorithm have been applied to stock market prediction, either by tuning parameters or experimenting with different base learners. …”
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The use of pretrained neural networks for solving the problem of reverse searching of X-ray images of prohibited items and substances by A. K. Volkov, L. V. Mironova, S. E. Potapova

“…The principal component analysis is used to reduce the dimensionality of the image feature vectors. The decision of whether the segmented image element is a prohibited item or substance is considered as a reverse search problem using the k-nearest neighbor algorithm. …”
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Optimizing machine learning methods for groundwater quality prediction: Case study in District Bagh, Azad Kashmir, Pakistan by Usman Basharat, Wenjing Zhang, Cuihong Han, Shoukat Husain Khan, Arshad Abbasi, Sehrish Mahroof, Shuxin Li

“…This study evaluates various base ML algorithms and stacking ensemble classifiers (meta-classifiers) using data from 90 groundwater samples collected in District Bagh, Azad Kashmir, Pakistan. …”
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Multi-objective optimization of process parameters for laser cladding of Cr3C2/15-5PH composite coatings on 20CrMnTi using RSM-CMOPSO-EWM-CV by Yanbin Du, Kaiyi Mao, Xin Lei, Wensheng Ma, Qiang Liang, Jian Tu

“…Subsequently, the CMOPSO algorithm was employed to optimize the process parameters in order to obtain a Pareto solution set. …”
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Dual objective multimodal transportation path optimization based on different carbon tax mechanisms under uncertain demand by Xu Zhang, Hongzhu Chen, Haiyan Zhang, Xumei Yuan

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Extraction of exact symbolic stationary probability formulas for Markov chains in finite space with application to production lines. part II: unveiling accurate formulas for very s... by Konstantinos S. Boulas, Georgios D. Dounias, Chrissoleon T. Papadopoulos

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