Elevating metaverse virtual reality experiences through network‐integrated neuro‐fuzzy emotion recognition and adaptive content generation algorithms by Oshamah Ibrahim Khalaf, Dhamodharan Srinivasan, Sameer Algburi, Jeevanantham Vellaichamy, Dhanasekaran Selvaraj, Mhd Saeed Sharif, Wael Elmedany

“…An inventive method that combines natural language processing adaptive content generation algorithms and neuro‐fuzzy‐based support vector machines natural language processing (SVM‐NLP) is proposed by researchers to meet this demand. …”
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Binary Classification of Customer’s Online Purchasing Behavior Using Machine Learning by Ahmad Aldelemy, Raed A. Abd-Alhameed

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Laser–Arc Welding Adaptive Model of Multi-Pre-Welding Condition Based on GA-BP Neural Network by Zesheng Wu, Zhaodong Zhang, Gang Song

“…In this study, laser–arc hybrid welding is used to perform butt welding on 6 mm Q345 steel in various assembly conditions, and we propose an adaptive model of the BP neural network optimized by a genetic algorithm (GA) for laser–arc welding. …”
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Leveraging Artificial Intelligence in Public Health: A Comparative Evaluation of Machine-Learning Algorithms in Predicting COVID-19 Mortality by Eric B. Weiser

“…Objective: This study aimed to evaluate and compare the predictive performance of four ML algorithms – K-Nearest Neighbors (KNN), Random Forest, Extreme Gradient Boosting (XGBoost), and Decision Tree – in estimating daily new COVID-19 deaths. …”
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Exploration of Machine Learning Models for Prediction of Gene Electrotransfer Treatment Outcomes by Alex Otten, Michael Francis, Anna Bulysheva

“…This study elucidates areas where predictive ML algorithms may ideally inform GET study design to accelerate optimization and improve efficiencies upon the further training of these models.…”
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Estimating Canopy Chlorophyll Content of Potato Using Machine Learning and Remote Sensing by Xiaofei Yang, Hao Zhou, Qiao Li, Xueliang Fu, Honghui Li

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An Adaptive Multi-Fidelity Surrogate Model for Uncertainty Propagation Analysis by Wei Xiao, Yingying Shen, Jiao Zhao, Luogeng Lv, Jiangtao Chen, Wei Zhao

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Low-Complexity Adaptive Chromatic Dispersion Estimation Scheme Using Machine Learning for Coherent Long-Reach Passive Optical Networks by Jin Li, Danshi Wang, Min Zhang

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Hyperspectral estimation of chlorophyll density in winter wheat using fractional-order derivative combined with machine learning by Chenbo Yang, Chenbo Yang, Meichen Feng, Juan Bai, Hui Sun, Rutian Bi, Lifang Song, Chao Wang, Yu Zhao, Wude Yang, Lujie Xiao, Meijun Zhang, Xiaoyan Song

“…Hyperspectral monitoring models for winter wheat ChD were constructed using 8 machine learning algorithms, including partial least squares regression, support vector regression, multi-layer perceptron regression, random forest regression, extra-trees regression (ETsR), decision tree regression, K-nearest neighbors regression, and gaussian process regression, based on the full spectrum band and the band selected by competitive adaptive reweighted sampling (CARS). …”
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Traffic identification of network business based on multi-layer cascade algorithm by Feng HUANG, Yao WANG, Li HUANG, Jiming YAO, Shidong LIU

“…The contradiction between traffic demand and network bandwidth is the main problem of the current network.Traffic management is one of the effective solutions,at the same time it can improve the quality of service of the network,and network traffic identification is the basis of fine traffic management.The traffic identification method of network business based on multi-layer cascade algorithm was proposed,after the research of network traffic identification and machine learning techniques.This method can adapt to the situation of the complex network traffic flow,and can balance the contradiction between the time performance and the accuracy of the machine learning algorithm.Furthermore the cascade algorithm of this method takes the cost imbalance into account,and takes more attention to the identification of important business,so it can help enhance user experience.…”
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Dynamic Error Modeling and Predictive Compensation for Direct-Drive Turntables Based on CEEMDAN-TPE-LightGBM-APC Algorithm by Manzhi Yang, Hao Ren, Shijia Liu, Bin Feng, Juan Wei, Hongyu Ge, Bin Zhang

“…Our methodology comprises four key stages: Complete Ensemble Empirical Mode Decomposition with Adaptive Noise (CEEMDAN)-based decomposition of historical error data, development of component-specific prediction models using Tree-structured Parzen Estimator (TPE)-optimized Light Gradient Boosting Machine (LightGBM) algorithms for each Intrinsic Mode Function (IMF), integration of component predictions to generate initial values, and application of the Adaptive Prediction Correction (APC) module to produce final predictions. …”
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A Novel Capacity Estimation Method for Lithium-Ion Batteries Based on the Adam Algorithm by Yingying Lian, Dongdong Qiao

“…In this paper, we propose multiple machine learning algorithms to estimate the capacity using the incremental capacity (IC) curve features, including the adaptive moment estimation (Adam) model, root mean square propagation (RMSprop) model, and support vector regression (SVR) model. …”
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RARE: right algorithm for the right errand; a multi-model machine learning-based approach for tourism routes and spots recommendation by Ling Luo

“…However, traditional static route-based algorithms struggle to adapt to the rapid expansion of the tourism industry, necessitating the development of dynamic, machine-learning-driven solutions. …”
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Stochastic and deterministic processes in Asymmetric Tsetlin Machine by Negar Elmisadr, Mohamed-Bachir Belaid, Anis Yazidi

“…This paper introduces a new approach to enhance the decision-making capabilities of the Tsetlin Machine (TM) through the Stochastic Point Location (SPL) algorithm and the Asymmetric Steps technique. …”
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Evaluation of Ecosystem Health Based on AWDO-SVR Algorithm in Shiyang River Basin by WANG Wenchuan, LI Lei, ZHENG Ye, XU Dongmei, XU Lei

“…This paper evaluates the ecological health of Shiyang River Basin by the adaptive wind-driven optimization (AWDO) algorithm and support vector regression (SVR) coupled algorithm for problems in health assessment of watershed ecosystem,finds the optimal parameters of support vector machine (SVM) by AWDO algorithm for uncertainty of parameters from SVM,proposes an evaluation model based on AWDO-SVR algorithm,and evaluates nine indexes such as water resource endowment,water resource development and utilization,and social and economic function of Shiyang River Basin by the model with advantages of fast and simple operation and no need of weight.The results show that the ecological health is sub-health for the upper reaches of Shiyang River,and morbid for the middle and lower reaches respectively.The evaluation result is the same as that of the variable set model,indicating that AWDO-SVR algorithm can be effectively applied to the ecosystem health evaluation of the river basin.…”
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AquaFlowNet a machine learning based framework for real time wastewater flow management and optimization by P. Prabu, Ala Saleh Alluhaidan, Romana Aziz, Shakila Basheer

“…Abstract This paper presents AquaFlowNet, a machine learning-based algorithm for real-time wastewater flow management. …”
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Prediction of Thyroid Classes Using Feature Selection of AEHOA Based CNN Model for Healthy Lifestyle by Rachappa Jopate, Piyush Kumar Pareek, DivyaJyothi M. G, Ariam Saleh Zuwayid Juma Al Hasani

Subjects: “…Adaptive Elephant Herd Optimization Algorithm, Convolutional Neural Network, Hyperthyroidism Imbalanced data, Machine Learning, Synthetic Minority Over-sampling Technique…”
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Optimal Adaptive Modeling of Hydrogen Polymer Electrolyte Membrane Fuel Cells Based on Meta-Heuristic Algorithms Considering the Membrane Aging Factor by Mohamed Ahmed Ali, Mohey Eldin Mandour, Mohammed Elsayed Lotfy

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Prediabetes risk classification algorithm via carotid bodies and K-means clustering technique by Rafael F. Pinheiro, Maria P. Guarino, Marlene Lages, Rui Fonseca-Pinto

“…In the search for methods to support early diagnosis, this article introduces a novel prediabetes risk classification algorithm (PRCA) for type-2 diabetes mellitus (T2DM), utilizing the chemosensitivity of carotid bodies (CB) and K-means clustering technique from the field of machine learning. …”
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Distinct morphometric features of cardiomyocytes isolated from mouse hypertrophy models: An ImageJ analysis combined with machine learning algorithms by Hoang Duc Minh Pham, Marie‐Thérèse Daher, Onnik Agbulut, Zhenlin Li, Ara Parlakian

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