Integrated remote sensing, machine learning and geospatial approach for site selection of sewage treatment plants in the metropolitan city by S. Rajalakshmi, S. Subathradevi, Abdulaziz G. Alghamdi, Hadeel Alsolai

“…A Random Forest (RF) algorithm was applied to enhance spatial prediction. …”
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Machinability Assessment and Multi-Objective Optimization of Graphene Nanoplatelets-Reinforced Aluminum Matrix Composite in Dry CNC Turning by Nikolaos A. Fountas, Dimitrios E. Manolakos, Nikolaos M. Vaxevanidis

“…The results indicated that the feed rate was the dominant parameter affecting both objectives, namely the main cutting force and surface roughness, while the NSGA-II algorithm was capable of delivering advantageous solutions for enhancing machinability with less than 10% error predictions when comparing simulated and actual machining results.…”
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China’s county-level monthly CO2 emissions during 2013–2021 by Ming Gao, Chaofan Tu, Miaomiao Liu, Jiandong Chen, Xingyu Chen, Hong Zou, Thomas Shiu Tong, Long Chen, Shuke Fu

“…After the main feature variables were identified, a hybrid regression algorithm combining deep neural networks and CatBoost was constructed to generate instrumental variable for predicting CO2 emissions. …”
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Research on Designing an Industrial Product-Service System with Uncertain Customer Demands by Fei Zhang, Liecheng Jia, Weizhen Han

“…This paper presents a design model that integrates an improved affinity propagation (AP) clustering algorithm, quality function development (QFD), and axiomatic design (AD). …”
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Wear monitoring method of water-lubricated polymer thrust bearing based on ultrasonic reflection coefficient amplitude spectrum by Changxiong Ning, Fei Hu, Wu Ouyang, Xinpin Yan, Dongling Xu

“…The effects of bearing parameters, objective function, and algorithm parameters on the identification results are simulated and analyzed. …”
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Antioxidants and Cognitive-Behavioral Therapy in Patients with Functional Dyspepsia by T. V. Sapozhnikova, S. A. Parfenov, T. E. Yesina, K. V. Sapozhnikov, A. N. Smirnov, A. A. Paulov, D. M. Rizakhanov, O. A. Rizakhanova

“…After comparing it with a threshold, the probability of a positive response to a combination of antioxidant and cognitive-behavioral therapy is estimated. The developed prediction algorithm is valid (sensitivity — 91 %, specificity — 73 %, accuracy — 84.8 %) and allows to optimize the definition of treatment tactics for a patient with functional dyspepsia.…”
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Optimization of Electric Vehicle Charging and Discharging Strategies Considering Battery Health State: A Safe Reinforcement Learning Approach by Shuifu Gu, Kejun Qian, Yongbiao Yang

“…First, a novel battery health status prediction model based on physics-informed hybrid neural networks (PHNN) is designed. …”
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Estimating shear strength of dredged soils for marine engineering: experimental investigation and machine learning modeling by Zheng Yao, Kaiwei Xu, Zejin Wang, Haodong Sun, Peng Cui, Peng Cui

“…Comparative analysis demonstrated that the LDA–BA–ANN configuration delivered the highest prediction precision and computational speed over traditional models. …”
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Detection of Pesticide Residues Using Three-Dimensional SERS Substrate Based on CNTs/Ag/AgNWs/SiO₂ by Jianjun Ding, Niansong Liu, Ganglin Wang, Naiyu Guo, Chao Sun

“…The experimental results indicated that the GA-BP algorithm achieved the training prediction accuracy of 92.5% for thiram, demonstrating good network performance. …”
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Modeling of Thermal Conductivity in a Medium with Phase Transition with a Moving Boundary of Phase Change by Mizonov V.E., Tikhonov A.I., Basova E.V., Mitrofanov A.V.

“…The significance of the results obtained consisted in the development of a simple but informative mathematical model of the media heat treatment kinetics with phase transformations, available for a direct use in the engineering practice. The proposed algorithm for constructing the model can be effectively used in prediction the open water pipes freezing in cold regions, in modeling the heat treatment of metals, in choosing the freezing modes of food products for a long-term storage, and other thermo-physical processes.…”
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Rolling Bearing Dynamics Simulation Information-Assisted Fault Diagnosis with Multi-Adversarial Domain Transfer Learning by Zhe Li, Zhidan Zhong, Zhihui Zhang, Wentao Mao, Weiqi Zhang

“…Firstly, the algorithm constructs both a global domain classifier and a subdomain classifier. …”
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Utilization of remote sensing and GIS for land use and land cover mapping in Wasit province, Iraq by Abdulkareem Meena K., Sabah Jaber Hussein

“…This study investigates the effectiveness of a supervised MLC classification algorithm to produce LULC maps of Wasit Governorate from multiple satellite images using remote sensing and GIS techniques, which is of great importance for earth observation applications, such as environmental monitoring and disaster prediction. …”
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A clustering fractional-order grey model in short-term electrical load forecasting by Xiang Yu, Lihua Lu, Jianming Qi, Yuchen Qian, Lisen Zhao, Chang Tan, Yangquan Chen, Zhigang Han

“…Hyper parameters of these equations are then sent to a global optimization algorithm to reduce predictive errors. Simulation results on two electricity datasets demonstrated that our algorithm can learn from datasets hyper parameters inside equations and produce forecast values efficiently. …”
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High-precision deformation monitoring and intelligent early warning for wellbore based on BDS/GNSS. by Jiang Li, Lei Dai, Keke Xu, Xinyu Mei, Yifu Liu, Jianlin Shi, Hebing Zhang

“…To address the complex deformation of wellbores influenced by surrounding coal mining operations, this study employed an improved modified least-squares ambiguity decorrelation (MLAMBDA) algorithm based on the double-difference model for high-frequency dynamic computation of Bei Dou System and Global Navigation Satellite System (BDS/GNSS) observation data. …”
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Compositional modeling of solution gas–oil ratio (Rs): a comparative study of tree-based models, neural networks, and equations of state by Aydin Larestani, Sara Sahebalzamani, Abdolhossein Hemmati-Sarapardeh, Ali Naseri

“…Among the tested models, the extra trees (ET) algorithm demonstrated superior performance, achieving an average absolute percent relative error (AAPRE) of approximately 3%, indicating its high reliability for Rs prediction. …”
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AI-Driven Particulate Matter Estimation Using Urban CCTV: A Comparative Analysis Under Various Experimental Conditions by Woochul Choi, Hongki Sung, Kyusoo Chong

“…All four experiments that excluded the nighttime, added the solar incidence angle variable, applied the distribution of PM per class, and removed the outlier removal algorithm showed high predictive power. In particular, the final experiment that satisfied all conditions, including the exclusion of nighttime, addition of solar incidence angle variable, and application of outlier removal algorithm, derived predictive values that are expected to be commercialized.…”
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Demand-Adapting Charging Strategy for Battery-Swapping Stations by Benjamín Pla, Pau Bares, Andre Aronis, Augusto Perin

“…An optimized charging policy is derived using dynamic programming (DP), assuming average battery demand and accounting for both the costs and emissions associated with electricity consumption. The proposed algorithm uses a prediction of the expected traffic in the area as well as the expected cost of electricity on the net. …”
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Estimating Economic Insights: A Machine Learning Method for Estimating the Shanghai Stock Exchange by Reza Seifi Majdar, Seyed Hadi Seyed Hatami

“…This work aims to create an accurate hybrid model for predicting stock prices which includes Adaptive Boosting, Slime mould algorithm, and Empirical mode decomposition (EMD) to forecast the stock market values. …”
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Cyber threat intelligence for smart grids using knowledge graphs, digital twins, and hybrid machine learning in SCADA networks by Nabeel Al-Qirim, Munir Majdalawieh, Anoud Bani-hani, Hussam Al Hamadi

“…This study presents a novel “Digital-twin and Machine Learning-based SCADA Cyber Threat Intelligence (DT-ML-SCADA-CTI)” approach, which utilizes an innovative algorithm to visualize and predict the effects of cyber-attacks, including FDIA, RTCI, and SRA, on SCADA systems. …”
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Assessing the generalization capabilities of TCR binding predictors via peptide distance analysis. by Leonardo V Castorina, Filippo Grazioli, Pierre Machart, Anja Mösch, Federico Errica

“…In this work, we introduce a novel approach for assessing the generalization capabilities of TCR binding predictors: the Distance Split (DS) algorithm. The DS algorithm controls the distance between training and testing peptides based on both sequence and structure, allowing for a more nuanced evaluation of model performance. …”
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