Prediction of Weight and Body Condition Score of Dairy Goats Using Random Forest Algorithm and Digital Imaging Data by Mateus Alves Gonçalves, Maria Samires Martins Castro, Eula Regina Carrara, Camila Raineri, Luciana Navajas Rennó, Erica Beatriz Schultz

“…Pearson’s correlation analysis and the Random Forest algorithm were performed. It was possible to predict BW using image features with an R² of 0.87, with D (22.14%), CW (18.93%) and BL (15.47%) being the most important variables. …”
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Prediction of Future State Based on Up-To-Date Information of Green Development Using Algorithm of Deep Neural Network by Liyan Sun, Li Yang, Junqi Zhu

“…In this study, the focus was on the development of green energy and future prediction for the consumption of current energy sources and green energy development using an improved deep learning (DL) algorithm. …”
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Exploiting the Regularized Greedy Forest Algorithm Through Active Learning for Predicting Student Grades: A Case Study by Maria Tsiakmaki, Georgios Kostopoulos, Sotiris Kotsiantis

“…In this study, we introduce an innovative approach that leverages the Regularized Greedy Forest (RGF) algorithm within an active learning framework to enhance student performance prediction. …”
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Groundwater level prediction using an improved SVR model integrated with hybrid particle swarm optimization and firefly algorithm by Sandeep Samantaray, Abinash Sahoo, Falguni Baliarsingh

“…In order to simulate GWL, five data-driven (DD) models, including the hybridization of support vector regression (SVR) with two optimisation algorithms i.e., firefly algorithm and particle swarm optimisation (FFAPSO), SVR-FFA, SVR-PSO, SVR and Multilayer perception (MLP), have been examined in the present study. …”
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The Short‐Time Prediction of the Energetic Electron Flux in the Planetary Radiation Belt Based on Stacking Ensemble‐Learning Algorithm by Rongxin Tang, Yuhao Tao, Jiahao Li, Zhou Chen, Xiaohua Deng, Haimeng Li

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Utilizing machine learning to predict MRI signal outputs from iron oxide nanoparticles through the PSLG algorithm by Fatemeh Hataminia, Anahita Azinfar

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TransferBAN-Syn: a transfer learning-based algorithm for predicting synergistic drug combinations against echinococcosis by Haitao Li, Haitao Li, Yuanyuan Chu, Yuanyuan Chu, Liyuan Jiang, Liyuan Jiang, Lei Li, Lei Li, GuoDong Lv, Yuansheng Liu, Chunhou Zheng, Chunhou Zheng, Yansen Su, Yansen Su

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Predicting emergency department admissions using a machine-learning algorithm: a proof of concept with retrospective study by Cyrielle Brossard, Christophe Goetz, Pierre Catoire, Lauriane Cipolat, Christophe Guyeux, Cédric Gil Jardine, Mahuna Akplogan, Laure Abensur Vuillaume

“…It seems interesting to be able to predict the admissions of patients in the ED. Aim The main objective of this study was to build and test a prediction tool for ED admissions using artificial intelligence. …”
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Research on prediction algorithm of college students' academic performance based on Bert-GCN multi-modal data fusion by Yan Wu

“…To this end, this study proposes a multimodal data fusion algorithm based on BERT-GCN, which can be used to predict the academic performance of college students more accurately and help college teaching. …”
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Improved Quantum Artificial Bee Colony Algorithm-Optimized Artificial Intelligence Models for Suspended Sediment Load Predicting by Peng Wei, Wang Yu

“…To evaluate the predictive capability, the models are compared with quantum bee colony algorithm-optimized AI models (QABC-SVR and QABC-ANN), genetic algorithm-optimized AI models (GA-SVR and GA-ANN) and traditional AI models (SVR and ANN). …”
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Prediction of pathological grade of oral squamous cell carcinoma and construction of prognostic model based on deep learning algorithm by Tingru Shao, Peirong Ni, Chun Wang, Jiahui Li, Xiaozhi Lv

“…Abstract The aim of this study is to establish a deep learning model for predicting the pathological grade of oral squamous cell carcinoma(OSCC) based on whole slide images (WSIs). …”
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A data-driven machine learning algorithm to predict the effectiveness of inulin intervention against type II diabetes by Shuheng Yang, Ralf Weiskirchen, Wenjing Zheng, Xiangxu Hu, Aibiao Zou, Zhiguo Liu, Hualin Wang

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Energy Efficiency in Smart Buildings through Prediction modeling and Optimization Using a Modified Whale Optimization Algorithm by El Assri Nasima, Ennejjar Mohammed, Jallal Mohammed Ali, Chabaa Samira, Zeroual Abdelouhab

“…In addition to predictive analysis, this study utilizes a Modified Whale Optimization Algorithm (MWOA) to optimize energy consumption. …”
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BP Neural Network Improved by Sparrow Search Algorithm in Predicting Debonding Strain of FRP-Strengthened RC Beams by Guibing Li, Tianyu Hu, Dawei Bai

“…In order to improve the accuracy of predicting the debonding strain of FRP-strengthened RC beams, a BP neural network model was developed based on the sparrow search algorithm (SSA). …”
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Research on 5G base station energy saving system based on DCNN-LSTM load prediction algorithm by Jianbin WANG, Shuchun WANG, Shangjin LIAO, Shuyuan SHI

“…With the rapid construction of the 5G wireless communication network, the energy consumption pressure of operators, and even the overall communication industry, is simultaneously highlighted.Achieving sustainable development of the industry through energy conservation and consumption reduction has become a new research direction for the current 5G network development.Taking the PRB rate as the load evaluation index, LSTM model was improved by using DCNN to extract the depth feature of the cell’s indicators.A set of DCNN-LSTM deep learning model that could predict the future value of PRB rate was proposed.On the basis of the improved algorithm, the network topology of the current 5G access network was optimized.An additional network element and its working system were designed.An intelligent energy-saving system, which ensured the network experience, of 5G base stations was realized.…”
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A New Hybrid Algorithm for Bankruptcy Prediction Using Switching Particle Swarm Optimization and Support Vector Machines by Yang Lu, Nianyin Zeng, Xiaohui Liu, Shujuan Yi

“…In this paper, a new hybrid algorithm combining switching particle swarm optimization (SPSO) and support vector machine (SVM) is proposed to solve the bankruptcy prediction problem. …”
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Improving prediction accuracy of open shop scheduling problems using hybrid artificial neural network and genetic algorithm by Mohammad Reza Komari Alaei, Reza Rostamzadeh, Kadir Albayrak, Zenonas Turskis, Jonas Šaparauskas

“…Furthermore, an examination of the average values of standard error revealed that the neural network model outperformed in terms of predictive accuracy. The estimated minimum time necessary for task completion, as determined by the neural network, was calculated to be 0.96699, facilitating an optimal condition for meeting the established objectives. …”
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Integration of Multiple Models with Hybrid Artificial Neural Network-Genetic Algorithm for Soil Cation-Exchange Capacity Prediction by Mahmood Shahabi, Mohammad Ali Ghorbani, Sujay Raghavendra Naganna, Sungwon Kim, Sinan Jasim Hadi, Samed Inyurt, Aitazaz Ahsan Farooque, Zaher Mundher Yaseen

“…In this study, a multiple model integration scheme supervised with a hybrid genetic algorithm-neural network (MM-GANN) was developed and employed to predict the accuracy of soil CEC in Tabriz plain, an arid region of Iran. …”
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Leveraging Azure Automated Machine Learning and CatBoost Gradient Boosting Algorithm for Service Quality Prediction in Hospitality by Avisek Kundu, Seeboli Ghosh Kundu, Santosh Kumar Sahu, Nitesh Dhar Badgayan

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Artificial Bee Colony Algorithm Based on the Division Between Exploration and Exploitation and Its Application in Esophageal Cancer Prediction by WANG Yingcong, YAN Jun, SUN Junwei, WANG Yanfeng

“…ObjectiveIn the artificial bee colony (ABC) algorithm, employed bees search the entire search space while onlooker bees concentrate their efforts near high-quality food sources. …”
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