Automatic Synthesis of Recurrent Neurons for Imitation Learning From CNC Machine Operators by Hoa Thi Nguyen, Roland Olsson, Oystein Haugen

“…AutoML approaches aim to automate this process, reducing human bias and improving accuracy and cost-effectiveness. …”
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A Novel Adaptive Cuboid Regional Growth Algorithm for Trunk–Branch Segmentation of Point Clouds from Two Fruit Tree Species by Yuheng Cao, Ning Wang, Bin Wu, Xin Zhang, Yaxiong Wang, Shuting Xu, Man Zhang, Yanlong Miao, Feng Kang

“…This method integrates a growth vector that is adaptively adjusted based on the growth trend of branches and a growth cuboid that is dynamically regulated according to branch diameters. …”
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An Iterative Pixel-Based Dimensional Voting Model for High Spatial-Resolution Image Classification by Muhamad Asyraf Mohd Pouzi, Haza Nuzly Abdull Hamed, Muhammad Razib Othman, Hishammuddin Asmuni, Mohd Adham Isa, Husni Ruslai

“…The findings indicate that Pixel-DMV simplifies the classification process by relying on a single dataset, reducing data preparation costs, and is suitable for frequent data collection tasks. …”
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A CGAN-based adversarial attack method for data-driven state estimation by Qi Wang, Jing Zhang, Jianxiong Hu, Shutan Wu, Shiyi Hou, Yi Tang

“…Simulation results demonstrate that the proposed method could compromise the state estimation process while evading bad data detection, all with reduced attack costs. …”
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High expression of long non-coding RNA ZEB1-AS1 promotes colorectal cancer cell proliferation partially by suppressing p15 expression by Huangbo Gong, Hao Wen, Xuhui Zhu, Yifan Lian, Xiaojun Yang, Zhuyin Qian, Jin Zhu

“…Collectively, ZEB1-AS1 has asignificant effect on colorectal cancer pathological process and serves as a valuable prognostic biomarker for colorectal cancer.…”
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Active learning based surrogate ensemble assisted multi-objective optimization framework for reservoir water-flooding optimization by Lian Wang, Liang Zhang, Rui Deng, Jianhua Qu, Hehua Wang, Liehui Zhang, Xing Zhao, Bing Xu, Xindong Lv, Caspar Daniel Adenutsi

“…In this proposed ALSA-MOPO method, three frequently-used surrogate models, the radial basis function network, Gaussian process regression, and support vector regression are adopted to construct the surrogate ensemble. …”
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Advanced long-term actual evapotranspiration estimation in humid climates for 1958–2021 based on machine learning models enhanced by the RReliefF algorithm by Ahmed Elbeltagi, Salim Heddam, Okan Mert Katipoğlu, Abdullah A. Alsumaiei, Mustafa Al-Mukhtar

“…AET was estimated using support vector machine (SVM), ensemble bagged and boosted trees, robust linear regression (RLR), and Matern 5/2 Gaussian process regression (M-GPR) models. …”
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Evaluation of machine learning-based regression techniques for prediction of diabetes levels fluctuations by Badriah Alkalifah, Muhammad Tariq Shaheen, Johrah Alotibi, Tahani Alsubait, Hosam Alhakami

“…To support this an Artificial Neural Network (ANN), Binary Decision Tree (BDT), Linear Regression (LR), Boosting Regression Tree Ensemble (BSTE), Linear Regression with Stochastic Gradient Descent (LRSGD), Stepwise (SW), Support Vector Machine (SVM), and Gaussian process regression (GPR) were investigated. …”
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Butterfly magnetoreception based neighbour awareness strategy protocol for autonomous aerial vehicles by Janjhyam Venkata Naga Ramesh, C. Dastagiraiah, Suraya Mubeen, W. Deva Priya, M. Kameswara Rao, B. H. K. Bhagat Kumar

“…However, navigating through high-density obstacle environments poses substantial challenges due to process overheads, dynamic environmental conditions, and scalability issues. …”
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Axial Capacity Estimation of FRP-strengthened Corroded Concrete Columns by Chandan Gupta, Harish Arora, Aman Kumar, Prashant Kumar, Nishant Raj Kapoor, Madhu Sharma

“…Considering the scarcity of reliable design guidelines for estimating the axial strength of RC columns considering corrosion effects, artificial neural network (ANN), Gaussian process regression (GPR), and support vector machine (SVM) techniques were employed. …”
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A review of machine learning and internet-of-things on the water quality assessment: Methods, applications and future trends by Gangani Dharmarathne, A.M.S.R. Abekoon, Madhusha Bogahawaththa, Janaka Alawatugoda, D.P.P. Meddage

“…Explainable AI (XAI) which can explain the decision making process of ML, is underutilised, appearing in only a few recent studies. …”
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SVR-Optimized ANN Model for Predicting Earthquake Risk in Electrical Substations Based on Disaster Datasets in the Aceh Region, Indonesia by Elvy Sahnur Nasution, Yuwaldi Away, Syahrial, Ira Devi Sara, Andri Novandri

“…This paper proposes a predictive model based on an Artificial Neural Network (ANN) optimized with Support Vector Regression (SVR) to predict seismic parameters as part of earthquake risk mitigation for substations. …”
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Emotion-Aware Ensemble Learning (EAEL): Revolutionizing Mental Health Diagnosis of Corporate Professionals via Intelligent Integration of Multi-Modal Data Sources and Ensemble Tech... by Gaurav Yadav, Mohammad Ubaidullah Bokhari, Saleh I. Alzahrani, Shadab Alam, Mohammed Shuaib

“…EAEL integrates machine learning and deep learning paradigms to process multimodal data, including facial expression analysis and typing pattern recognition, offering a holistic evaluation of emotional well-being. …”
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Sustainable Polyurethane-Based Polymer Concrete: Mechanical and Non-destructive Properties with Machine Learning Technique by S. I. Haruna, Han Zhu, Yasser E. Ibrahim, Jian Yang, AIB Farouk, Jianwen Shao, Musa Adamu, Omar Shabbir Ahmed

“…The experimental datasets from mechanical and NDT tests were utilized to train machine learning (ML) models, including multilinear regression (MLR), artificial neural network (ANN), support vector machine (SVM), Gaussian regression process (GPR), and stepwise regression (SWR) models for estimating the f c. …”
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Evaluation of oxidative stress status and antioxidant defense status of athletes after inclusion of a special product for sportive nutrition in their food ration by R. Rakhmanov, T. Blinova, L. Strakhova, S. Kolesov, V. Troshin, R. Hyairov

“…The sportsmen of experimental group additionally received the «product for sportive nutrition» in their food ration. The training process was the same in both groups; it was divided into three stages. …”
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Development and validation of a machine learning‐based model of ischemic stroke risk in the Chinese elderly hypertensive population by Xiaoyue Lyu, Jie Liu, Yingying Gou, Shengli Sun, Jing Hao, Yali Cui

“…The final model, eXtreme gradient boosting, was identified as having superior performance than the other 9 classifers (random forest, Gaussian process, multilayer perceptron, logistic regression, support vector machine, K‐nearest neighbor, decision tree, Gaussian naive bayes, and ensemble model), with area under the receiver‐operating characteristic curves of 0.97 and 0.94 for the test and external validation sets, respectively. …”
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Detection of Escherichia coli Using Bacteriophage T7 and Analysis of Excitation‑Emission Matrix Fluorescence Spectroscopy by Nicharee Wisuthiphaet, Huanle Zhang, Xin Liu, Nitin Nitin

“…For example, the Gaussian Process model achieved an accuracy of 92% in detecting different concentration levels of live E. coli. …”
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Temperature affects the sorption of trace metals by macro- and microplastics within marine intertidal sediments: insights from a long-term laboratory-based study by Tamara N. Kazmiruk, Juan José Alava, Juan José Alava, Eirikur Palsson, Leah I. Bendell

“…Macro- and microplastics and trace metals are significant pollutants in the marine environment and have been reported in all ecosystems around the world. The process of sorption/desorption of trace metals by macro- and microplastics is influenced by various factors, including the morphological characteristics of macro- and microplastics, their adsorption capacity, and environmental conditions. …”
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Optimization of carbon peak path in Fujian Province based on sparrow search algorithm by CAI Huang, LIN Xiaoyu*, CAI Zhiling, ZHONG Yiwen, ZHONG Fenglin

“…In response to the urgent global challenge of carbon emission reduction, reliable pathways to carbon peaking are of significant importance for the implementation of carbon reduction in China. However, the process of carbon dioxide emissions involves numerous influencing factors, and the combinations of their change rates are diverse. …”
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Improving rainfall forecasting using deep learning data fusing model approach for observed and climate change data by Farhan Amir Fardush Sham, Ahmed El-Shafie, Wan Zurina Binti Wan Jaafar, S. Adarsh, Mohsen Sherif, Ali Najah Ahmed

“…For the 3-day forecasting interval, Exponential Gaussian Process Regression (Exponential GPR) marginally outperformed Long Short-Term Memory (LSTM), with Mean Absolute Error (MAE), Mean Squared Error (MSE), and Root Mean Squared Error (RMSE) values of 15.84, 547.04, and 23.39, respectively. …”
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