Implementation of Fisher-Yates Shuffle and Fuzzy Tsukamoto in Nusantara Educational Game by Khairul Insan Karim, Chairunnisa Lamasitudju, Ryfial Azhar, Fizar Syafaat, Anisa Yulandari

Subjects: “…education game…”
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Predictive Modeling of Climate-Driven Crop Yield Variability Using DSSAT Towards Sustainable Agriculture by Safa E. El-Mahroug, Ayman A. Suleiman, Mutaz M. Zoubi, Saif Al-Omari, Qusay Y. Abu-Afifeh, Heba F. Al-Jawaldeh, Yazan A. Alta’any, Tariq M. F. Al-Nawaiseh, Nisreen Obeidat, Shahed H. Alsoud, Areen M. Alshoshan, Fayha M. Al-Shibli, Rakad Ta’any

“…In contrast, under SSP3-7.0 (2070–2100), rising maximum temperatures became the primary constraint, highlighting the growing risk of heat stress. Predictive accuracy was higher in precipitation-dominated scenarios (R² = 0.81) than in temperature-dominated cases (R² = 0.65–0.73), reflecting greater complexity under extreme warming. …”
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Machine learning models for predicting the risk of depressive symptoms in Chinese college students by Chengfu Yu, Xiangxuan Kong, Weijie Yu, Xingcan Ni, Jing Chen, Xiaoyan Liao

“…Given the limitations of traditional linear models in managing high-dimensional data, this study employed machine learning techniques to predict depressive symptoms.MethodData were collected from 1,635 Chinese college students and included 38 sociodemographic, psychological, and social variables. …”
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Deep learning-based crop health enhancement through early disease prediction by Venkata Santhosh Yakkala, Krishna Vamsi Nusimala, Badisa Gayathri, Sriya Kanamarlapudi, S. S. Aravinth, Ayodeji Olalekan Salau, S. Srithar

“…By introducing AI-driven systems into agricultural practices, this study aims to revolutionize disease identification, prediction, and management. The overarching objective is to minimize crop losses and enhance agricultural productivity. …”
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User Evaluation of a Machine Learning-Based Student Performance Prediction Platform by Hoti Arbër H., Zenuni Xhemal, Hamiti Mentor, Ajdari Jaumin

“…The integration of machine learning in education has opened new possibilities for predicting student performance and enabling early interventions. …”
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Application of Machine Learning Methods for Employee Turnover Prediction Based on Open Data by A. N. Kazinets

“…An analysis of existing approaches to predicting staff turnover is conducted, the need to use modern machine learning algorithms is substantiated. …”
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Power management in isolated microgrids using machine learning-based robust model predictive control by Chou-Yi Hsu, Amit Ved, Hannah Jessie Rani R, Zayd Ajsan Balsem, Nora Rashid Najem, Abhayveer Singh, P․Sasi Kiran, Ankita Aggarwal, Satish Kumar Samal, Alireza Kamranfar

“…This paper presents a new control strategy based on a type-2 neural fuzzy robust model predictive control (MPC) for an isolated microgrid system that include various types of renewable energy sources (RES) such as photovoltaics (PVs), wind turbines (WTs), fuel cells (FCs) and battery energy storage systems (BESSs). …”
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Criteria for predicting the initiation of rolling contact fatigue damage in the railway wheels and rails by V. I. Sakalo, A. V. Sakalo

“…The methods of modeling allow predict the possibility of initiation of the fatigue cracks during operation with the sufficient accuracy in the short time. …”
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Gradient boosting for yield prediction of elite maize hybrid ZhengDan 958. by Oumnia Ennaji, Sfia Baha, Leonardus Vergutz, Achraf El Allali

“…Using a recent dataset of over 1700 maize yield data pairs, our evaluation included a spectrum of algorithms. Our results show robust prediction accuracy for all algorithms. …”
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Predicting safety attitudes in aviation maintenance using machine learning: An exploratory study by Christos Emexidis, Anna V. Chatzi, Kyriakos I. Kourousis

“…The Random Forest machine learning algorithm was utilised to identify the relationships and to enable predictions. …”
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Recent advances in machine learning for defects detection and prediction in laser cladding process by X.C. Ji, R.S. Chen, C.X. Lu, J. Zhou, M.Q. Zhang, T. Zhang, H.L. Yu, Y.L. Yin, P.J. Shi, W. Zhang

“…As a fundamental component of artificial intelligence, machine learning has gained considerable prominence within the domain of laser cladding in recent years. By employing algorithms to analyze data, discern patterns and regularities, rendering predictions and decisions, machine learning has significantly influenced various aspects of laser cladding processes. …”
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Development of a deep learning system for predicting biochemical recurrence in prostate cancer by Lu Cao, Ruimin He, Ao Zhang, Lingmei Li, Wenfeng Cao, Ning Liu, Peisen Zhang

“…Finally, patient-level artificial intelligence models were developed by integrating deep learning -generated pathology features with several machine learning algorithms. Results The BCR prediction system demonstrated great performance in the testing cohort (AUC = 0.911, 95% Confidence Interval: 0.840–0.982) and showed the potential to produce favorable clinical benefits according to Decision Curve Analyses. …”
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A review of a priori regression models for warfarin maintenance dose prediction. by Ben Francis, Steven Lane, Munir Pirmohamed, Andrea Jorgensen

“…A number of a priori warfarin dosing algorithms, derived using linear regression methods, have been proposed. …”
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Predicting postoperative neurological outcomes of degenerative cervical myelopathy based on machine learning by Shuai Zhou, Shuai Zhou, Shuai Zhou, Shuai Zhou, Zexiang Liu, Zexiang Liu, Zexiang Liu, Haoge Huang, Haoge Huang, Haoge Huang, Hanxu Xi, Xiao Fan, Xiao Fan, Xiao Fan, Yanbin Zhao, Yanbin Zhao, Yanbin Zhao, Xin Chen, Xin Chen, Xin Chen, Yinze Diao, Yinze Diao, Yinze Diao, Yu Sun, Yu Sun, Yu Sun, Hong Ji, Feifei Zhou, Feifei Zhou, Feifei Zhou

“…After training and optimizing multiple ML algorithms, we generated a model with the highest area under the receiver operating characteristic curve (AUROC) to predict short-term outcomes following DCM surgery. …”
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Multispectral Sensors and Machine Learning as Modern Tools for Nutrient Content Prediction in Soil by Rafael Felippe Ratke, Paulo Roberto Nunes Viana, Larissa Pereira Ribeiro Teodoro, Fábio Henrique Rojo Baio, Paulo Eduardo Teodoro, Dthenifer Cordeiro Santana, Carlos Eduardo da Silva Santos, Alan Mario Zuffo, Jorge González Aguilera

“…This soil analysis technique requires more refined correlation models for accurate prediction.…”
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Prediction and Stage Classification of Pressure Ulcers in Intensive Care Patients by Machine Learning by Mürsel Kahveci, Levent Uğur

“…This increases the need for more sensitive, predictive and integrative systems. The aim of this study was to classify pressure ulcer stages (Stages I–IV) with high accuracy using machine learning algorithms using demographic, clinical and laboratory data of ICU patients and to evaluate the model performance at a level that can be integrated into clinical decision support systems. …”
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Optimizing SVC placement for enhanced voltage stability using a novel index and hybrid ABC-PSO algorithm by Hafizur Rahman, Roman Mia, Mustafizur Rahman, Md. Faiyaj Ahmed Limon, Md. Shahid Iqbal, Md. Fahad Jubayer, Md. Rabiul Karim, Md. Janibul Alam Soeb

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Developing a Model to Predict the Effectiveness of Vaccination on Mortality Caused by COVID-19 by Malihe Niksirat, Javad Tayyebi, Seyedeh Fatemeh Javadi, Adrian Marius Deaconu

“…Machine learning (ML) algorithms offer promising tools for predicting vaccine effectiveness and aiding public health decisions. …”
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Long-term prediction for VBR video traffic based on wavelet packet decomposition by CHEN Jian1, WEN Ying-you1, ZHAO Da-zhe1, LIU Ji-ren1

“…Long-term prediction is one of the most difficult problems in the area of VBR video traffic prediction.As to the time variation,non-linearity and long range dependence in VBR video traffic trace,a novel method of feature based on multi-scale decomposition was proposed.On the analysis of the time-frequency distribution characteristics of the video trace,the wavelet packets which have the trait of arbitrary distinction and decomposition are selected.After space partition of wavelet packets,the best wavelet packet basis for feature extraction is picked out.Based on the best basis,it can do fast arbitrary multi-scale WPT（wavelet packet transform）,and obtain each higher dimension wavelet coefficients matrix.And then wavelet coefficients prediction is proposed based on LS-SVM and LMS algorithms.The long-term pre-diction of VBR video traffic is obtained through reverse wavelet transforms on the predicted wavelet coefficients.Nu-merical and simulation results are provided to validate the claims.…”
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Prediction of traditional Chinese medicine for diabetes based on the multi-source ensemble method by Bin Yang, Qingyun Chi, Xiang Li, Jinglong Wang

“…The compound dataset from the TCMSP database is then used as testing data to predict and screen the active ingredients. The frequencies of occurrences of medicinal herbs corresponding to these three algorithms are obtained, each containing an active ingredient list. …”
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