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

“…In the proposed fuzzy system, settings are adjusted using a restricted Boltzmann machine (RBM) and contrastive divergence (CD) algorithm, and are then used for MPC optimization. …”
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S100A7 as a predictive biomarker in malignant transformation of oral epithelial dysplastic lesions by Jeffrey Soparlo, Lachlan McLean, Christina McCord, Linda Jackson-Boeters, Michael Shimizu, Michael Robinson, Wanninayake M. Tilakaratne, Mark R. Darling

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Predictive Archaeological Modeling with MaxEnt (Late Roman Settlements in The Upper Don Basin Case) by D. V. Sarychev, G. L. Zemtsov

“…The paper is devoted to an archaeological predictive modeling technique with GIS and machine learning based on maximal entropy algorithm (MaxEnt). …”
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A Type‐3 Fuzzy‐Based Model Predictive Control Approach for Management of Constant Energy by Man‐Wen Tian, Lixing Zhu, Mohammad Hosein Sabzalian, Jafar Tavoosi, Amirhosein Khosravi Sarvenoee, Pierpaolo D'Urso, Ebrahim Ghaderpour, Ardashir Mohammadzadeh

“…To tackle this challenge, a disturbance observer and a continuous‐time model predictive control based on type‐3 fuzzy logic systems (T3‐FLSs) are applied to the bidirectional DC‐DC converter. …”
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Indoor Air Wellness: A Predictive Model for Pollution Control Using Advanced AI Techniques by Kalyan Chatterjee, Muntha Raju, Bhoomeshwar Bala, U. Nikitha, Gampala Prabhas, Naim Ahmad, Ayman Qahmash, Wade Ghribi, Bernardo Lemos, Saurav Mallik

“…The model excels in dynamic environments by refining the accuracy of the proposed Kal-ANN algorithm achieving a predictive accuracy of up to 96. 55%, a root mean square error, a Mean Absolute Error, and a Mean Squared Prediction Error as low as 9.85, 6.12, and <inline-formula> <tex-math notation="LaTeX">$3.15~g/m$ </tex-math></inline-formula>. …”
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Predictive model for sarcopenia in patients with non-small cell lung cancer and malignant pleural effusion by Hengxing Gao, Xuexue Zou, Meng Fan, Mingwei Chen

“…A nomogram was developed to facilitate personalized prediction of sarcopenia for individual patient. The ROC curve demonstrated that the nomogram model incorporating these predictive factors achieved an area under the curve (AUC) of 0.889, indicating its discriminatory power in predicting sarcopenia. …”
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Mining privacy-preserving association rules using transaction hewer allocator and facile hash algorithm in multi-cloud environments by D. Dhinakaran, S. Gopalakrishnan, D. Selvaraj, M.S. Girija, G. Prabaharan

“…The complexities involved in the mining of frequent itemsets led us to introduce the Apriori with Tid Reduction (ATid) algorithm considering scalability and computational operational improvements to the mining process due to the Tid Reduction concept. …”
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Hybrid System for Fault Tolerance in Selective Compliance Assembly Robot Arm: Integration of Differential Gears and Coordination Algorithms by Claudio Urrea, Pablo Sari, John Kern

“…Nonlinear Model Predictive Controllers (NLMPCs) and Adaptive Sliding Mode Control (ASMC) were compared, with NLMPC excelling in stability and ASMC in precision. …”
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Integrating AI Deep Reinforcement Learning With Evolutionary Algorithms for Advanced Threat Detection in Smart City Energy Management by Fenghua Liu, Xiaoming Li

“…The integration of Deep Reinforcement Learning (DRL) with Evolutionary Algorithms (EAs) represents a significant advancement in optimizing smart city energy operations, addressing the inherent uncertainties and dynamic conditions of urban environments. …”
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The Application of Near-Infrared Spectroscopy Combined with Chemometrics in the Determination of the Nutrient Composition in Chinese <i>Cyperus esculentus</i> L. by Xiaobo Jiao, Dongliang Guo, Xinjun Zhang, Yunpeng Su, Rong Ma, Lewen Chen, Kun Tian, Jingyu Su, Tangnuer Sahati, Xiahenazi Aierkenjiang, Jingjing Xia, Liqiong Xie

“…In addition, to further enhance the prediction performance of the models, various preprocessing and variable selection algorithms were utilized to optimize the prediction models. …”
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Combination of Evolutionary Algorithms and Direct Search Approaches for Improving the Dynamic Performance of Grid Connected Solar Power System by Amit Verma, Prabhakar Tiwari, Desh Deepak Sharma

“…The comparison showed by using Genetic Algorithm-Simulated Annealing, peak overshoot in DC-link voltage is 829.3 V while peak overshoot in DC-link voltage is 1 052 V when DC-link voltage is controlled by manual tuning of PI as well as significant reduction in peak time and settling time in DC-link voltage. …”
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Low-cost fabrication and comparative evaluation of machine learning algorithms for flexible PDMS-based hexagonal patch antenna by Srivatsan Sarvesan, Mettu Goutham Reddy, S. S. Karthikeyan, Praveen K. Sekhar

“…To accelerate the design process and determine the most effective model for predicting optimal geometrical parameters that yield improved impedance matching at the target frequency, four supervised machine learning algorithms including Random Forest, XGBoost, CatBoost and LightGBM were evaluated and compared. …”
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Examining the empathy levels of medical students using CHAID analysis by Nesrin Hark Söylemez

“…CHAID analysis was employed to identify the key predictors influencing empathy levels, whereas machine learning algorithms were utilized to classify and predict individuals' empathy levels. …”
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Forecasting Lake Nokoué Water Levels Using Long Short-Term Memory Network by Namwinwelbere Dabire, Eugene C. Ezin, Adandedji M. Firmin

“…In this study, the Long Short-Term Memory (LSTM) network, a state-of-the-art algorithm dedicated to time series, is applied to predict the daily water level of Lake Nokoué in Benin. …”
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OPTIMIZATION OF TURNING PARAMETERS USING AN ALGORTIM BASED ON COMBINED LINEAR AND BINARY SEARCH METHODS by DAN GEORGE PRUTICA, GHEORGHE BRABIE, BOGDAN CHIRITA

“… Optimization of cutting parameters in machining operations is a complex task requiring extensive knowledge and experience to reach the maximum potential for cost reductions in manufacturing. Through the work presented in this paper a cutting parameters optimization algorithm for roughing and finishing turning has been realized. …”
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Artificial intelligence in traditional Chinese medicine: advances in multi-metabolite multi-target interaction modeling by Yu Li, Xiangjun Liu, Jingwen Zhou, Fengjiao Li, Yuting Wang, Qingzhong Liu

“…To enhance the reliability and scalability of AI in TCM target prediction, future research should prioritize continuous optimization of the AI algorithms using zero-shot learning, end-to-end architectures, and self-supervised contrastive learning.…”
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Modelling the effect of vaccination on the spread of COVID-19 via a novel evolutionary ensemble learning algorithm by Mohammad Hassan Tayarani Najaran

“…This paper proposes a modelling algorithm that takes as input the percentage of the vaccinated population and the policies taken by governments and generates as output a prediction of the number of newly infected cases. …”
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Hybrid Models for Forecasting Allocative Localization Error in Wireless Sensor Networks by Guo Li, Hongyu Sheng

“…The approach utilizes Radial Basis Function (RBF) models enhanced with advanced optimization algorithms, including Coot Optimization Algorithm (COA), Smell Agent Optimization (SAO), and Northern Goshawk Optimization (NGO) to improve ALE prediction accuracy. …”
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Optimization of design parameters and 3D-printing orientation to enhance the efficiency of topology-optimized components in additive manufacturing by Dame Alemayehu Efa, Dejene Alemayehu Ifa

“…In addition to optimizing 3D printing orientation, this study uses Response Surface Methodology (RSM) and optimization algorithms to optimize design parameters such as safety factor and thickness for predicting stress and deformation in topology optimization. …”
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LEVERAGING MACHINE LEARNING ALGORITHMS TO IDENTIFY POTENTIAL GEOSITES FOR GEOTOURISM PROMOTION IN ZIZ UPPER WATERSHED IN SOUTHEASTERN MOROCCO by Lahbib NAIMI, Mohamed MANAOUCH, Abdeslam JAKIMI

“…Subsequently, the machine learning algorithm, namely Bagging was employed to develop predictive model. …”
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