Adaptive drive-based integration technique for predicting rheological and mechanical properties of fresh gangue backfill slurry by Chaowei Dong, Jianfei Xu, Nan Zhou, Jixiong Zhang, Hao Yan, Zejun Li, Yuzhe Zhang

“…Analysis demonstrates that the particle swarm optimal (PSO) algorithm based on adaptive adjustment strategy can effectively optimize the hyperparameters of support vector regression (SVR), and the MC-PSO-SVR model exhibits better predictive capability (R2> 0.88) and lower error coefficients (MAE, RSE, and RMSE values approaching 0) and narrower widths of 95 % confidence intervals for yield stress, plastic viscosity, fluidity, and UCS. …”
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Research on Wind Power Grid Integration Power Fluctuation Smoothing Control Strategy Based on Energy Storage Battery Health Prediction by Bin Cheng, Jiahui Wu, Guancheng Lv, Zhongbo Li

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Noise Reduction in CWRU Data Using DAE and Classification with ViT by Jun-gyo Jang, Soon-sup Lee, Se-yun Hwang, Jae-chul Lee

“…These technological advancements have played a significant role in the dramatic growth of the predictive maintenance market for mechanical equipment, prompting active research on noise removal techniques and classification algorithms for the accurate determination of the causes of equipment failure. …”
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Efficient and Constant Time Modular Reduction With Generalized Mersenne Primes by Serdar S. Erdem, Sezer S. Erdem

“…The proposed modular reduction algorithms handle the final reduction by two subtractions in constant time to avoid timing attacks.…”
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TEMPTED: time-informed dimensionality reduction for longitudinal microbiome studies by Pixu Shi, Cameron Martino, Rungang Han, Stefan Janssen, Gregory Buck, Myrna Serrano, Kouros Owzar, Rob Knight, Liat Shenhav, Anru R. Zhang

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Enhancing sustainability in dairy industry: Blockchain-based waste reduction by Diana Hawashin, Khaled Salah, Raja Jayaraman, Raja Wasim Ahmad, Salil Kanhere, Ernesto Damiani

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Electricity Losses in Focus: Detection and Reduction Strategies—State of the Art by Daniela F. Niste, Radu Tîrnovan, Sorin Pavel, Horia Beleiu, Cziker Andrei, Marius Misaroș

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Enhanced prediction of heating value of municipal solid waste using hybrid neuro-fuzzy model and decision tree-based feature importance assessment by Oluwatobi Adeleke, Obafemi O. Olatunji, Tien-Chien Jen, Iretioluwa Olawuyi

“…This study proposes a hybrid network of adaptive neuro-fuzzy inference system (ANFIS) with genetic algorithm (GA) to predict the higher heating value (HHV) of municipal solid waste (MSW). …”
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Performance Predictions of Solar-Assisted Heat Pumps: Methodological Approach and Comparison Between Various Artificial Intelligence Methods by Minghui Ma, Oguzhan Pektezel, Vincenzo Ballerini, Paolo Valdiserri, Eugenia Rossi di Schio

Subjects: “…data-driven intelligent algorithms…”
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Integration of multi agent reinforcement learning with golden jackal optimization for predicting average localization error in wireless sensor networks by K. Lakshmi Prabha, Hanan Abdullah Mengash, Hamed Alqahtani, Randa Allafi

Subjects: “…Multi agent reinforcement learning algorithm…”
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Comparative study on RF-BP model prediction of mining water-conducting fracture zone height in Binchang Coal Mine by Yadong JI, Xuan LIU, Kaipeng ZHU, Chunhu ZHAO, Kai LI, Chenhan YUAN, Panpan LI, Pengzhen YAN

“…Back propagation neural network, genetic algorithm and particle swarm optimization were used to optimize BP neural network and random forest algorithm to carry out regression fitting for the interpolated data. …”
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Risk prediction of QTc prolongation occurrence in cancer patients treated with commonly used oral tyrosine kinase inhibitors: machine learning modeling or conventional statistical... by Hsiang-Wen Lin, Tien-Chao Lin, Chien-Ning Hsu, Tzu-Pei Yeh, Yu-Chieh Chen, Liang-Chih Liu, Chen-Yuan Lin

“…The backward LR method and seven ML algorithms were applied to train and test the prediction models. …”
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Mobile application based on KDD to predict high-crime areas and promote sustainability in citizen security in a district of Lima-Perú by Hugo Vega-Huerta, Javier Vilca Velasquez, Nicolas Anicama Espinoza, Gisella Luisa Elena Maquen-Niño, Luis Guerra-Grados, Jorge Pantoja-Collantes, Oscar Benito-Pacheco, Juan Carlos Lázaro-Guillermo, Adegundo Camara-Figueroa, Javier Cabrera-Díaz, Rubén Gil-Calvo, Frida López-Córdova

“…The data mining process follows the KDD methodology, which includes the stages of selection, preprocessing, transformation, data mining, evaluation and knowledge consolidation. Machine learning algorithms, such as Random Forest and Gradient Boosting, were used to make these predictions. …”
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Advancing overbreak prediction in drilling and blasting tunnel using MVO, SSA and HHO-based SVM models with interpretability analysis by Yulin Zhang, Jian Zhou, Jialu Li, Biao He, Danial Jahed Armaghani, Shuai Huang

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QSAR Model for Prediction of some Non-Nucleoside Inhibitors of Dengue Virus Serotype 4 NS5 using GFA-MLR Approach by Samuel Adawara, Gideon Shallangwa, Paul Mamza, Abdulkadir Ibrahim

“…Thus, the model can be used to predict the activity of new chemicals within its applicability domain. …”
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CFD investigation and ANN prediction of heat transfer coefficient for fully developed turbulent air flow around double V-baffle turbulators by Abdulaziz Alasiri, H.E. Fawaz

“…The ANN model demonstrates excellent predictive performance, yielding values close to 1 for R2 and r, along with extremely low values for MSE, MAPE, MSLE, and log-cosh loss (0.01, 0.6 %, 0.001, and 0.01, respectively), demonstrating the ANN model's high predictive accuracy.…”
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Lithium-Ion Battery Health State Prediction Based on Improved War Optimization Assisted-Long and Short-Term Memory Network by Xiankun Wei, Mingli Mo, Silun Peng

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Metaheuristic Prediction Models for Kerf Deviation in Nd-YAG Laser Cutting of AlZnMgCu1.5 Alloy by Arulvalavan Tamilarasan, Devaraj Rajamani

“…A detailed investigation was conducted to examine the effects of various parameters on kerf deviation. The metaheuristic algorithms (i.e., Giant Trevally Optimizer—GTO; and Zebra Optimization Algorithm—ZOA) were implemented to determine the optimum process parameters for producing the best performance measures. …”
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Continuous prediction of knee joint angle in lower limbs based on sEMG: a method combining an improved ZOA optimizer and attention-enhanced GRU by Jian Lv, Binhao Huang, Ligang Qiang

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A Comparative Study between Different Machine Learning Algorithms for Estimating the Vehicular Delay at Signalized Intersections by Yazan Alatoom, Abdallah Al-Hamdan

Subjects: “…machine learning for delay prediction…”
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