Transformer–BiLSTM Fusion Neural Network for Short-Term PV Output Prediction Based on NRBO Algorithm and VMD by Xiaowei Fan, Ruimiao Wang, Yi Yang, Jingang Wang

“…And finally, the VMD-NRBO-Transformer-BiLSTM prediction model and hyperparameter selection are evaluated by the NRBO algorithm. …”
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Prediction of Chlorophyll-a Concentration Distribution Using Generative Adversarial Network (GAN) Algorithm on Processed Remote Sensing Images by Wattaqwa Amira Zul’Ilmi, Jaya Indra, Iqbal Muhammad

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A Meta-Heuristic Algorithm-Based Feature Selection Approach to Improve Prediction Success for Salmonella Occurrence in Agricultural Waters by Murat Canayaz, Murat Demir, Zeynal Topalcengiz

“…Recently, the performances of various algorithms have been tested for the prediction of indicator bacteria population and pathogen occurrence in agricultural water sources. …”
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Bayesian optimization with Optuna for enhanced soil nutrient prediction: a comparative study with genetic algorithm and particle swarm optimization by Bamidele A. Dada, Nnamdi I. Nwulu, Seun O. Olukanmi

“…Optimizing soil nutrient prediction models is important for achieving maximum agricultural output and sustainability while also ensuring effective resource management and environmental protection, as demonstrated by a case study in Johannesburg, South Africa. …”
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Applying genetic algorithm to extreme learning machine in prediction of tumbler index with principal component analysis for iron ore sintering by Senhui Wang

“…The results showed that an improvement in predictive accuracy can be obtained by the GA-ELM approach, and the accuracy of TI prediction is 81.85% for absolute error under 0.7%.…”
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Prediction of train wheel diameter based on Gaussian process regression optimized using a fast simulated annealing algorithm. by Xiaoying Yu, Hongsheng Su, Zeyuan Fan, Yu Dong

“…An algorithm to predict train wheel diameter based on Gaussian process regression (GPR) optimized using a fast simulated annealing algorithm (FSA-GPR) is proposed in this study to address the problem of dynamic decrease in wheel diameter with increase in mileage, which affects the measurement accuracy of train speed and location, as well as the hyper-parameter problem of the GPR in the traditional conjugate gradient algorithm. …”
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Prediction of Crop Yield by Support Vector Machine Coupled with Deep Learning Algorithm Procedures in Lower Kulfo Watershed of Ethiopia by Abebe Temesgen Ayalew, Tarun Kumar Lohani

“…Sensible and judicious utilization of water for agriculture in conjunction with prediction techniques increases the crop yield. The Ethiopian economy relies on and is exclusively dependent on agricultural-based activities. …”
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A Sensor Data Prediction and Early-Warning Method for Coal Mining Faces Based on the MTGNN-Bayesian-IF-DBSCAN Algorithm by Mingyang Liu, Xiaodong Wang, Wei Qiao, Hongbo Shang, Zhenguo Yan, Zhixin Qin

“…Experimental results indicate that the MTGNN outperforms comparative algorithms, such as CrossGNN and FourierGNN, in prediction accuracy, with the mean absolute error (MAE) being as low as 0.00237 and the root mean square error (RMSE) maintained below 0.0203 across different sensor locations (T0, T1, T2). …”
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Improving machine learning algorithm for risk of early pressure injury prediction in admission patients using probability feature aggregation by Shu-Chen Chang, Shu-Mei Lai, Mei-Wen Wu, Shou-Chuan Sun, Mei-Chu Chen, Chiao-Min Chen

“…Objective Pressure injuries (PIs) pose a significant concern in hospital care, necessitating early and accurate prediction to mitigate adverse outcomes. Methods The proposed approach receives multiple patients records, selects key features of discrete numerical based on their relevance to PIs, and trains a random forest (RF) machine learning (ML) algorithm to build a predictive model. …”
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An efficient method for predicting temperature field of PC beams with CSWs using thermocouple numerical analysis and random forest algorithm by Haiping Zhang, Hao Long, Fanghuai Chen, Yuan Luo, Xinhui Xiao, Yang Deng, Naiwei Lu, Yang Liu

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Vortex-Induced Vibration Performance Prediction of Double-Deck Steel Truss Bridge Based on Improved Machine Learning Algorithm by Yang Yang, Huiwen Hou, Gang Yao, Bo Wu

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Modeling and Numerical Prediction on Mechanical Behaviors of Hybrid Fiber Reinforced Polymer Bio Composites Using Fuzzy Logic Algorithm by Vinoth Viswanathan, Sathiyamurthy Subbarayan, Ananthi Narayanaswamy, Devi Panneerselvam, Prabhakaran Jayasankar

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Prediction of Earthquake Death Toll Based on Principal Component Analysis, Improved Whale Optimization Algorithm, and Extreme Gradient Boosting by Chenhui Wang, Xiaotao Zhang, Xiaoshan Wang, Guoping Chang

“…To address the challenges of small sample sizes, high dimensionality, and strong nonlinearity in earthquake fatality prediction, this paper proposes an integrated modeling approach (PCA-IWOA-XGBoost) combining Principal Component Analysis (PCA), the Improved Whale Optimization Algorithm (IWOA), and Extreme Gradient Boosting (XGBoost). …”
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Machine Learning for the Prediction of Acute Kidney Injury in Critically Ill Patients With Coronary Heart Disease: Algorithm Development and Validation by Yike Li, Mingyang Xiao, Yaqian Li, Lulu Lv, Shanshan Zhang, Yuhui Liu, Juan Zhang

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A Genetic algorithm aided hyper parameter optimization based ensemble model for respiratory disease prediction with Explainable AI by Balraj Preet Kaur, Harpreet Singh, Rahul Hans, Sanjeev Kumar Sharma, Chetna Sharma, Md. Mehedi Hassan

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Prediction of chloride concentration in concrete under multi-salt environment: Optimization of integrated algorithm based on MSCPO and interpretability analysis by Daming Luo, Kanglei Du, Ditao Niu

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NGBoost algorithm-based prediction of mechanical properties of a hot-rolled strip and its interpretability research with ANOVA values by Hongyi Wu, Jinwen Jin, Zhiwei Li

“…The study focused on predicting tensile strength, yield strength, and elongation of hot-rolled strip steel and compared the predictive results with those obtained from the gradient boosting algorithm, Lasso regression, and decision tree algorithms. …”
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Study on risk factors of impaired fasting glucose and development of a prediction model based on Extreme Gradient Boosting algorithm by Qiyuan Cui, Jianhong Pu, Wei Li, Yun Zheng, Jiaxi Lin, Lu Liu, Peng Xue, Jinzhou Zhu, Mingqing He

“…ObjectiveThe aim of this study was to develop and validate a machine learning-based model to predict the development of impaired fasting glucose (IFG) in middle-aged and older elderly people over a 5-year period using data from a cohort study.MethodsThis study was a retrospective cohort study. …”
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Predicting the Cetane Number of Biodiesel using two AI-Models: the Gradient-based ANN and ANN Optimized by Genetic Algorithm by Hadis Tanha, Fatemeh Bashipour

“…They were the gradient-based artificial neural network (GB-ANN) and the multi-layer-perceptron ANN optimized by the genetic algorithm (GA-ANN) for the first time. The three input variablesof the model for predicting the target variable of the biodiesel CN are the average number of carbon atoms, average number of double bonds, and average molecular weight of the fatty acid methyl esters. …”
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Novel machine learning algorithm in risk prediction model for pan-cancer risk: application in a large prospective cohort by Chi-Pang Wen, Xifeng Wu, Qingfeng Hu, Huakang Tu, Shan Pou Tsai, David Ta-Wei Chu

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