Intelligent classification and prediction of students’ mental health in online learning environments using boosting algorithm and LIWC features by Xiaomin Xu, Tianrong Zhang

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Enhanced Localization in Wireless Sensor Networks Using a Bat-Optimized Malicious Anchor Node Prediction Algorithm by Balachandran Nair Premakumari Sreeja, Gopikrishnan Sundaram, Marco Rivera, Patrick Wheeler

“…To address this challenge, we propose the security-aware localization using bat-optimized malicious anchor prediction (BO-MAP) algorithm. This approach utilizes a refined bat optimization algorithm to improve both the precision of localization and the security of WSNs. …”
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Research on the Prediction Model of Wheel Set Failure Rate for Urban Rail Trains Based on IPSO-BP Algorithm by HE Deqiang, SUN Yi, MENG Jiwei, LIU Jianren

Subjects: “…failure rate prediction…”
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Predicting the Feasibility of Phenol Extraction from Water in Different Solvents Using the NRTL Model and a Genetic Algorithm by Nardjess Bouneb, Mouna Talbi, Amani Elgouacem, Abir Mezen

“…The predicted results are in agreement with experimental phase equilibrium data. …”
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A Linear Regression Prediction-Based Dynamic Multi-Objective Evolutionary Algorithm with Correlations of Pareto Front Points by Junxia Ma, Yongxuan Sang, Yaoli Xu, Bo Wang

“…Specifically, when the DMOP environment changes, this paper first constructs a spatio-temporal correlation model between various key points of the PF based on the linear regression algorithm; then, based on the constructed model, predicts a new location for each key point in the new environment; subsequently, constructs a sub-population by introducing the Gaussian noise into the predicted location to improve the generalization ability; and then, utilizes the idea of NSGA-II-B to construct another sub-population to further improve the population diversity; finally, combining the previous two sub-populations, re-initializing a new population to adapt to the new environment through a random replacement strategy. …”
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A Novel Approach for Blast-Induced Flyrock Prediction Based on Imperialist Competitive Algorithm and Artificial Neural Network by Aminaton Marto, Mohsen Hajihassani, Danial Jahed Armaghani, Edy Tonnizam Mohamad, Ahmad Mahir Makhtar

“…The scope of this study is to predict flyrock induced by blasting through a novel approach based on the combination of imperialist competitive algorithm (ICA) and artificial neural network (ANN). …”
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A novel strain-based bone-fracture healing algorithm is able to predict a range of healing outcomes by George T. Morgan, Lucas Low, Arul Ramasamy, Arul Ramasamy, Arul Ramasamy, Spyros D. Masouros

“…This study introduces a novel, strain-based fracture-healing algorithm designed to predict a wide range of healing outcomes, including both successful unions and non-unions. …”
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Predicting liver metastasis in pancreatic neuroendocrine tumors with an interpretable machine learning algorithm: a SEER-based study by Jinzhe Bi, Yaqun Yu

“…We applied 10 different machine learning algorithms to develop models for predicting the risk of liver metastasis in PaNETs patients. …”
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Presenting the AI models in predicting the settlement of earth dams using the results of spatiotemporal clustering and k-means algorithm by Behrang Beiranvand, Taher Rajaee, Mehdi Komasi

“…Therefore, the settlement location of the studied dam was determined using the results of the k-means clustering algorithm in the aforementioned AI models. The high accuracy of the results of the proposed method confirms the proper performance of using AI models in predicting and diagnosing the settlement of earthen dams using the results of k-means spatiotemporal clustering algorithm. …”
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Implementation of Taguchi and Genetic Algorithm Techniques for Prediction of Optimal Part Dimensions for Polymeric Biocomposites in Fused Deposition Modeling by Raman Kumar, Jasgurpreet Singh Chohan, Sandeep Singh, Shubham Sharma, Yadvinder Singh, S. Rajkumar

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Evaluating GRU Algorithm and Double Moving Average for Predicting USDT Prices: A Case Study 2017-2024 by Rahmat Rizky, Munirul ula, Zara Yunizar

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Rapid and direct discovery of functional tumor specific neoantigens by high resolution mass spectrometry and novel algorithm prediction by Huajian Tian, Guifei Li, Cookson K.C. Chiu, E. Li, Yuzong Chen, Ting Zhu, Min Hu, Yanjie Wang, Suping Wen, Jiajia Li, Shuangxue Luo, Zhicheng Chen, Huimei Zeng, Nan Zheng, Jinyong Wang, Weijun Shen, Xi Kang

“…By combining this approach with our proprietary AI-based prediction algorithm and high-throughput in vitro functional validation, we can generate patient-specific neoantigen candidates within six weeks, accelerating personalized tumor vaccine development.…”
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Prediction of caesarean section birth using machine learning algorithms among pregnant women in a district hospital in Ghana by Frederick Osei Owusu, Helena Addai-Manu, Esther Serwah Agbedinu, Emmanuel Konadu, Lydia Asenso, Mercy Addae, Joseph Osarfo, Brenda Abena Ampah, Douglas Aninng Opoku

“…Despite machine learning algorithms offering a more robust approach to predicting/diagnosing a health-related problem, research on their use in determining CS birth is scarce in sub-Saharan Africa. …”
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SAER : Comparison of Rule Prediction Algorithms on Constructing a Corpus for Taxation Related Tweet Aspect-Based Sentiment Analysis by Annisa Mufidah Sopian, Ridwan Ilyas, Fatan Kasyidi, Asep Id Hadiana

“…In this research, we propose SAER, a Syntactic Aspect-opinion Extraction and Rule prediction, that used language rule-based approach using syntactic features for aspect and opinion extraction, and we compare several algorithm for rule prediction such as Random Forest Regression, Decision Tree Regression, K-Nearest Neighbor Regression (KNN), Linear Regression, Support Vector Regression (SVR), and Extreme Gradient Boosting Regression (XGBoost) that can generate rules with a tree-based approach. …”
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Predictive Model of Granular Fertilizer Spreading Deposition Distribution Based on GA-GRNN Neural Network by Lilian Liu, Guobin Wang, Yubin Lan, Xinyu Xue, Suming Ding, Huizheng Wang, Cancan Song

“…The particle deposition distribution data under different operating parameters were obtained by EDEM simulation and data superposition methods, and a generalized regression neural network (GRNN) based on a genetic algorithm (GA) was used to establish the prediction model of particle deposition, which was validated by bench test. …”
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Improving lameness detection in cows: A machine learning algorithm application by Elma Dervić, Caspar Matzhold, Christa Egger-Danner, Franz Steininger, Peter Klimek

“…A Random Forest classifier, using input features selected by the Boruta algorithm, was used for the prediction task; effects of individual features were further assessed using partial dependence plots. …”
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AEA-YOLO: Adaptive Enhancement Algorithm for Challenging Environment Object Detection by Abdulrahman Kariri, Khaled Elleithy

“…A lightweight Parameter Prediction Network (PPN) containing only six thousand parameters predicts scene-adaptive coefficients for a differentiable Image Enhancement Module (IEM), and the enhanced image is then processed by a standard YOLO detector, called the Detection Network (DN). …”
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Comprehensive review of dimensionality reduction algorithms: challenges, limitations, and innovative solutions by Aasim Ayaz Wani

“…We outline solutions such as intrinsic dimensionality estimation, robust neighborhood graphs, fairness-aware embeddings, scalable algorithms, and automated tuning. Drawing on case studies from bioinformatics, vision, language, and Internet of Things analytics, we offer a practical roadmap for deploying dimensionality reduction methods that are scalable, interpretable, and ethically sound—advancing responsible artificial intelligence in high-stakes applications.…”
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Dimensionality Reduction Algorithms in Machine Learning: A Theoretical and Experimental Comparison by Ashish Kumar Rastogi, Swapnesh Taterh, Billakurthi Suresh Kumar

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Dimensionality Reduction using Hybrid Algorithms and Their Application to Remote Sensing Data by Maha Hasso, Mona Siddiq

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