A Hybrid Particle Swarm Optimization-Tuning Algorithm for the Prediction of Nanoparticle Morphology from Microscopic Images by Abhishek Singh, Thaseem Thajudeen

“…Various 3-dimensional properties including hydrodynamic diameter and mobility diameter of the retrieved structures are then compared with the properties of the aggregate used to form the candidate projection image, to test the suitability of the algorithm. Results show that the hybrid algorithm can closely predict the 3-dimensional structures from the projection images with less than 10% difference in the predicted 3-dimensional properties including mobility diameter and radius of gyration.…”
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Fixed Depth Control Strategy for Remotely Operated Vehicle Based on Improved Model Predictive Control Algorithm by Shuo YANG, Honghui WANG, Xinyu LIU, Xin FANG, Guanghao LI, Guijie LIU

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Application of machine learning algorithms and SHAP explanations to predict fertility preference among reproductive women in Somalia by Jamilu Sani, Salad Halane, Abdiwali Mohamed Ahmed, Mohamed Mustaf Ahmed

“…Predictor variables included sociodemographic factors, such as age, education, parity, wealth, residence, and distance to health facilities. Seven ML algorithms were evaluated for predictive performance, with Random Forest emerging as the optimal model based on metrics such as accuracy, precision, recall, F1-score, and the Area Under the Receiver Operating Characteristic Curve (AUROC). …”
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Performance Analysis of Battery State Prediction Based on Improved Transformer and Time Delay Second Estimation Algorithm by Bo Gao, Xiangjun Li, Fang Guo, Xiping Wang

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Prediction of effective moment of inertia for hybrid FRP-steel reinforced concrete beams using the genetic algorithm by A. Kheyroddin, F. Maleki

“…In this paper, we proposed a new equation for estimating the effective moment of inertia of hybrid FRP-steel reinforced concrete (RC) beams on the basis of the genetic algorithm and experimental results.The genetic algorithm is used to optimize the percent error between experimental and analytical responses. …”
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Precision forecasting for hybrid energy systems using five deep learning algorithms for meteorological parameter prediction by Ceren Ceylan, Zehra Yumurtacı

“…Although the deep learning-based meteorological forecasting is significantly studied in literature, most of the current literature applies single-algorithm based on each individual energy source and less multi-algorithm based on comparative studies on multiple architectures as applied to integrated hybrid systems. …”
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Performance of predictive algorithms in estimating the risk of being a zero-dose child in India, Mali and Nigeria by Sebastian Bauhoff, John Tucker, Arpita Biswas

“…There is little evidence on how to effectively and efficiently identify and target such ‘zero-dose’ (ZD) children.Methods We examined how well predictive algorithms can characterise a child’s risk of being ZD based on predictor variables that are available in routine administrative data. …”
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Study for Predicting Land Surface Temperature (LST) Using Landsat Data: A Comparison of Four Algorithms by Elhadi K. Mustafa, Yungang Co, Guoxiang Liu, Mosbeh R. Kaloop, Ashraf A. Beshr, Fawzi Zarzoura, Mohammed Sadek

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Utilizing machine learning algorithms for predicting Anxiety-Depression Comorbidity Syndrome in Gastroenterology Inpatients (ADCS-GI) by Min Tan, Jinjin Zhao, Yushun Tao, Uroosa Sehar, Yan Yan, Qian Zou, Qing Liu, Long Xu, Zeyang Xia, Lijuan Feng, Jing Xiong

“…Conclusion Machine learning algorithms can be used to identify ADCS among gastroenterology patients. …”
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Predicting the sonication energy for focused ultrasound surgery treatment of breast fibroadenomas using machine learning algorithms by Mengdi Liang, Yuelin Liu, Yue Huang, Ge Ma, Xu Han, Shuaikang Li, Jing Hang, Hui Xie, Lin Chen, Xiaoan Liu, Shui Wang, Tiansong Xia

“…Three machine learning algorithms were applied for feature selection. Then, all the selected features were used for the construction of the prediction model via four machine learning algorithms. …”
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Elevator fault precursor prediction based on improved LSTM-AE algorithm and TSO-VMD denoising technique. by Hao Cao, Xiaoyan Du

“…This study proposes an advanced elevator fault precursor prediction method integrating Variational Mode Decomposition (VMD), Bidirectional Long Short-Term Memory (BILSTM), and an Autoencoder with an Attention Mechanism (AEAM), collectively referred to as the VMD-BILSTM-AEAM algorithm. …”
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Firefly Algorithm-Based Artificial Neural Network to Predict the Shear Strength in FRP-Reinforced Concrete Beams by Mohammad Nikoo, Babak Aminnejad, Alireza Lork

“…This study uses 198 samples from the literature to predict the shear strength of 139 training samples and 59 testing samples. …”
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Predicting body weight in Ross 308 broiler chickens using a data mining algorithm approach by L Bila

“…This study aimed to use multivariate adaptive regression splines (MARS) and classification and regression tree (CART) data mining algorithms to predict the live body weights of Ross 308 male and female chickens from their morphological traits, and to compare the predictive performances of these two approaches. …”
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Prediction and Analysis of Train Passenger Load Factor of High-Speed Railway Based on LightGBM Algorithm by Bing Wang, Peixiu Wu, Quanchao Chen, Shaoquan Ni

“…It is verified that LightGBM algorithm of machine learning proposed in this paper has higher prediction accuracy than the traditional models, and its scientific and accurate prediction can provide an important reference for the calculation of passenger ticket revenue, operation benefit analysis, etc.…”
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Use of Machine Learning Algorithms to Predict Almen (Shot Peening) Intensity Values of Various Steel Materials by Murat İnce, Hatice Varol Özkavak

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PM2.5 Prediction Using Genetic Algorithm-Based Feature Selection and Encoder-Decoder Model by Minh Hieu Nguyen, Phi Le Nguyen, Kien Nguyen, Van An Le, Thanh-Hung Nguyen, Yusheng Ji

“…Our approach’s novelty is to utilize the genetic algorithm (GA) and an encoder-decoder (E-D) model for PM2.5 prediction. …”
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Prediction and optimization of acoustic absorption performance of quasi-Helmholtz acoustic metamaterials based on LightGBM algorithm by Jianxin Xu, Weikang Mao, Xiaoqian Yu, Bingfei Liu

“…This thesis aims to optimize and predict the acoustic absorption performance of quasi-Helmholtz acoustic metamaterials by using LightGBM algorithm in machine learning. …”
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355 Validation of an artificial intelligence Algorithm for predicting diagnosis-related groups in a community health system by Angela Muhanga, King Jason, Xsolis Mueller, Jennifer L. Sanger, Julie M. Bartlett, Brian N. Manz, James W. Spiten, Matthew J. Overgaard, Shauna M. Wang Hanyin

“…This algorithm, a 1D convolutional neural network, predicts DRGs based on clinical documentation. …”
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Classification Prediction of Jujube Variety Based on Hyperspectral Imaging: A Comparative Study of Intelligent Optimization Algorithms by Quancheng Liu, Jun Zhou, Zhaoyi Wu, Didi Ma, Yuxuan Ma, Shuxiang Fan, Lei Yan

“…The GWO-SVM-SG1st model achieved the highest classification accuracy, with 94.641% on the prediction sets. This study showcases the potential of combining hyperspectral imaging with intelligent optimization algorithms, offering an effective solution for jujube variety classification.…”
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Data-Driven Optimization Method for Recurrent Neural Network Algorithm: Greenhouse Internal Temperature Prediction Model by Kwang Cheol Oh, Sunyong Park, Seok Jun Kim, La Hoon Cho, Chung Geon Lee, Dae Hyun Kim

“…The optimal amount of data was determined to be between three and seven days, with an average model r² of 0.8811 and an RMSE of 2.056 for the gated recurrent unit algorithm. This study verified the possibility of developing a predictive model for the internal environment of a greenhouse based on weather data from outside. …”
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