Optimized dual NURBS curve interpolation for high-accuracy five-axis CNC path planning by Yi Xu, Mohd Hairi Mohd Zaman, Feng Zhou

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Assessment of Hull and Propeller Degradation Due to Biofouling Using Tree-Based Models by Nikos Themelis, George Nikolaidis, Vasilios Zagkas

“…The power prediction models are data-driven based on machine learning algorithms. …”
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Assessment model of ozone pollution based on SHAP-IPSO-CNN and its application by Xiaolei Zhou, Xingyue Wang, Ruifeng Guo

“…Then three mainstream machine learning models are compared for SHAP analysis to obtain the significance results of relevant features. …”
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An Assist-as-Needed Control Strategy Based on a Subjective Intention Decline Model by Hao Yan, Fangcao Zhang, Xingao Li, Chenchen Zhang, Yunjia Zhang, Yongfei Feng

“…The subjective intention decline module collects surface electromyography (sEMG) data during patient training and optimizes support vector machine (SVM) using quantum particle swarm optimization (QPSO) algorithms to establish a subjective intention decline model. …”
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Machine Learning and SHAP-Based Analysis of Deforestation and Forest Degradation Dynamics Along the Iraq–Turkey Border by Milat Hasan Abdullah, Yaseen T. Mustafa

“…Model interpretability was further improved through the application of SHapley Additive exPlanations (SHAP) to estimate variable contributions and a Generalized Additive Model (GAM) to elucidate complex nonlinear interactions. …”
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Optimization of a resilient circular closed-loop supply chain network under uncertainty by Samira Mehrabi, Hassan Mina, Shahryar Sorooshian

“…The results derived from implementing the developed optimization model in the real world and conducting the sensitivity analysis process denote the effectiveness and accuracy of the developed optimization model and solution method.…”
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Thermal errors in high-speed motorized spindle: An experimental study and INFO-GRU modeling predictions by Zhaolong Li, Kai Zhao, Haonan Sun, Yongqiang Wang, Bangxv Wang, JunMing Du, Haocheng Zhang

“…The novelty of this study lies in two improvements: firstly, the number of temperature measurement points is optimized by combining a clustering algorithm with a correlation coefficient method, reducing the amount of calculation and the risk of data coupling in the prediction; secondly, the GRU model optimized by the INFO algorithm is applied to the field of electric spindles for the first time, effectively analyzing the dynamic relationship between temperature and thermal expansion. …”
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Maximizing steel slice defect detection: Integrating ResNet101 deep features with SVM via Bayesian optimization by Prabira Kumar Sethy, Laxminarayana Korada, Santi Kumari Behera, Akshay Shirole, Rajat Amat, Aziz Nanthaamornphong

“…This paper addresses the challenge of classifying steel sheets into distinct defect categories by presenting a robust method that leverages deep learning and advanced optimization techniques. We propose a novel approach that utilizes the ResNet101 model to extract deep features, which are then classified using a support vector machine (SVM). …”
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Optimizing Input Feature Sets Using Catch-22 and Personalization for an Accurate and Reliable Estimation of Continuous, Cuffless Blood Pressure by Rajesh S. Kasbekar, Srinivasan Radhakrishnan, Songbai Ji, Anita Goel, Edward A. Clancy

“…Herein, we demonstrate how optimized machine learning using the Catch-22 features, when applied to the photoplethysmogram waveform and personalized with direct BP data through transfer learning, can accurately estimate systolic and diastolic BP. …”
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Prediction of the Therapeutic Response to Neoadjuvant Chemotherapy for Rectal Cancer Using a Deep Learning Model by Shunsuke Kubota, Taiichi Wakiya, Hajime Morohashi, Takuya Miura, Taishu Kanda, Masashi Matsuzaka, Yoshihiro Sasaki, Yoshiyuki Sakamoto, Kenichi Hakamada

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Data-Driven Modeling and Enhancement of Surface Quality in Milling Based on Sound Signals by Paschalis Charalampous

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COMPARATIVE ANALYSIS OF NEURAL NETWORK MODELS FOR THE PROBLEM OF SPEAKER RECOGNITION by Vladyslav Kholiev, Olesia Barkovska

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Experimental study on DEM parameters calibration for organic fertilizer by the particle swarm optimization − backpropagation neural networks by Fandi Zeng, Limin Liu, Yinzeng Liu, Hongbin Bai, Chunxiao Li, Zhihuan Zhao

“…The previously identified important variables were optimized by the Central Composite Design test. The regression fitting models of the BP neural network have been developed from the data set derived from the Central Composite Design test results. …”
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Modeling the compressive strength behavior of concrete reinforced with basalt fiber by Kennedy C. Onyelowe, Ahmed M. Ebid, Shadi Hanandeh, Viroon Kamchoom, Paul Awoyera, Siva Avudaiappan

“…Abstract This research investigates the compressive strength behavior of basalt fiber-reinforced concrete (BFRC) using machine learning models to optimize predictions and enhance its practical applications. …”
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Enhancing revenue generation in Bangladesh’s FinTech sector: a comprehensive analysis of real-time predictive customer behavior modeling in AWS using a hybrid OptiBoost-EnsembleX m... by Avijit Chowdhury

“…The investigation utilized a range of machine learning algorithms, such as random forest, support vector machine (SVM), XGBoost, CatBoost, and LightGBM, to develop models. …”
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An artificial intelligence model to predict mortality among hemodialysis patients: A retrospective validated cohort study by Zhong Peng, Shuzhu Zhong, Xinyun Li, Fengyi Yu, Zixu Tang, Chunyuan Ma, Zihao Liao, Song Zhao, Yuan Xia, Haojun Fu, Wei Long, Mingxing Lei, Zhangxiu He

“…The machine learning algorithms used to develop the models for the training group included logistic regression (LR), decision tree (DT), extreme gradient boosting machine (eXGBM), neural network (NN), and support vector machine (SVM). …”
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Consideration of the geomechanical state of a fractured porous reservoir in reservoir simulation modelling by Yurii A. Kashnikov, Denis V. Shustov, Sergei Yu. Yakimov

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A multi-objective supply chain model for disaster relief optimization using neutrosophic programming and blockchain-based smart contracts by Alisha Roushan, Amrit Das, Anirban Dutta, Uttam Kumar Bera

“…The model leverages Dijkstra’s algorithm to identify the shortest emergency routes and integrates Neutrosophic Compromise Programming (NCP) and the Weighted Sum Method (WSM) to optimize drone deployment for cost-effectiveness and timely intervention. …”
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Simplifying Field Traversing Efficiency Estimation Using Machine Learning and Geometric Field Indices by Gavriela Asiminari, Lefteris Benos, Dimitrios Kateris, Patrizia Busato, Charisios Achillas, Claus Grøn Sørensen, Simon Pearson, Dionysis Bochtis

“…This study aimed to simplify field efficiency estimation by training machine learning regression algorithms on data generated from a farm management information system covering a combination of different field areas and shapes, working patterns, and machine-related parameters. …”
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An artificial intelligence optimization of NOx conversion efficiency under dual catalytic mechanism reaction based on multi-objective gray wolf algorithm by Zhiqing Zhang, Zicheng He, Yuguo Wang, Feng Jiang, Weihuang Zhong, Bin Zhang, Yanshuai Ye, Zibin Yin, Dongli Tan

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