Multiple objectives escaping bird search optimization and its application in stock market prediction based on transformer model by Dedai Wei, Zimo Wang, Minyu Qiu, Juntao Yu, Jiaquan Yu, Yurun Jin, Xinye Sha, Kaichen Ouyang

“…This study first validates the performance of MOEBS through a series of multi-objective benchmark tests on standard problem sets such as ZDT, DTLZ, and WFG, comparing it with other multi-objective optimization algorithms (e.g., MOMVO, MSSA, and MOEAD) using evaluation metrics such as GD, Spacing, IGD, and HV for comprehensive analysis. …”
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A hybrid model combining environmental analysis and machine learning for predicting AI education quality by Xinyu Ren

“…Therefore, in this study, firstly, by dividing the macro environment into three different parts, including external, intermediate, and internal, a set of corrective measures in the university teaching and learning management in the background of AI education is proposed, and also the effects of their application in the management of teaching and learning in universities were discussed. Also, in order to evaluate the quality of AI training programs in higher education, a new approach based on the multilayer perceptron (MLP) algorithm was presented in which the capuchin search algorithm (CapSA) was used to adjust the weight vector of the neural network. …”
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Speech Emotion Recognition under White Noise by Chengwei HUANG, Guoming CHEN, Hua YU, Yongqiang BAO, Li ZHAO

“…Two speech enhancement algorithms are introduced for improved emotion classification. …”
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Tennis Timing Assessment by a Machine Learning-Based Acoustic Detection System: A Pilot Study by Lucio Caprioli, Amani Najlaoui, Francesca Campoli, Aatheethyaa Dhanasekaran, Saeid Edriss, Cristian Romagnoli, Andrea Zanela, Elvira Padua, Vincenzo Bonaiuto, Giuseppe Annino

“…Moreover, this system has proven effective in evaluating the technical skills of a group of players on the court and highlighting their areas for improvement, showing significant potential for practical applications in player training and performance analysis. …”
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Artificial intelligence as a transforming factor in motility disorders–automatic detection of motility patterns in high-resolution anorectal manometry by Miguel Mascarenhas, Francisco Mendes, Joana Mota, Tiago Ribeiro, Pedro Cardoso, Miguel Martins, Maria João Almeida, João Rala Cordeiro, João Ferreira, Guilherme Macedo, Cecilio Santander

“…A dataset of 701 HR-ARM exams from a tertiary center, classified according to London Classification, was used to develop and test multiple machine learning (ML) algorithms. The exams were divided in a training and testing dataset with a 80/20% ratio. …”
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Review of Demand Response-based Optimal Scheduling of Electric and Thermal Integrated Energy Systems by Jingshan MO, Guangxian YAN, Na SONG, Mingyang YUAN

“…However, the long offline training time for machine learning algorithms requires further optimization. …”
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Detección y diagnóstico de fallas en motores mediante el análisis de vibraciones aplicando técnicas de inteligencia artificial. by Jair Elías Araujo Vargas, Dilan Yesid Franklin Coronel, Victor Manuel Arias Ruiz

“…Therefore, the performance of different artificial intelligence algorithms in the field of fault detection and diagnosis using vibration analysis in motors was evaluated. …”
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Durability prediction of sustainable marine concrete under freeze-thaw cycles using multi-objective machine learning models by Aïssa Rezzoug, Ali H. AlAteah, Sadiq Alinsaif, Sahar A. Mostafa

“…Evaluation metrics included R², MAE, MSE, RMSE, and MARE, with model ranking as follows: MOO > ANFIS > CNN > GA-ANN. …”
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DETECTION OF KERATOCONUS DISEASE DEPENDING ON CORNEAL TOPOGRAPHY USING DEEP LEARNING by Aseel Abdulhasan Hashim, Mahdi Mazinani

“…It is not a widely prevalent disease, with a research gap caused by the absence of standardized datasets for model training and evaluation. This work presents a novel dataset, which strengthens the CNN model's resilience and creates standards for assessing keratoconus diagnostic techniques. …”
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Spatiotemporal Gap‐Filling of NASA Deep Blue Satellite Aerosol Optical Depth Over the Contiguous United States (CONUS) Using the UNet 3+ Architecture by Jeffrey S. M. Lee, S. Marcela Loría‐Salazar, Heather A. Holmes, Andrew M. Sayer

“…Abstract Due to sensor and algorithmic constraints, satellite aerosol optical depth (AOD) retrievals are spatially incomplete and have gaps caused by clouds and bright surfaces. …”
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Machine learning-based predictive model for acute pancreatitis-associated lung injury: a retrospective analysis by Zhaohui Du, Qiaoling Ying, Yisen Yang, Huicong Ma, Hongchang Zhao, Jie Yang, Zhenjie Wang, Chuanming Zheng, Shurui Wang, Qiang Tang

“…This study aims to develop a prediction model for the diagnosis of APALI based on machine learning algorithms.MethodsThis study included data from the First Affiliated Hospital of Bengbu Medical College (July 2012 to June 2022), which were randomly categorized into the training and testing set. …”
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Active Learning for Medical Article Classification with Bag of Words and Bag of Concepts Embeddings by Radosław Pytlak, Paweł Cichosz, Bartłomiej Fajdek, Bogdan Jastrzębski

“…Different versions of the bag of concepts are compared with bag of words, as well as with combined representations, including both word-based and concept-based features. The evaluation uses the support vector machine, naive Bayes, and random forest algorithms and is performed on datasets from 15 systematic medical literature review studies. …”
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Integrating Multi-Layer Perceptron Regression with Innovative Optimization for Accurate Building Cooling Load Prediction by Subhiya Zeynalli, Baharak Eslami

“…Through a hybridization technique with two cutting-edge optimization algorithms, the Brown Bear Optimization Algorithm (BBOA) and the Non-Monopolize Search Algorithm (NMSA), it sets out to explore its optimization potential. …”
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Forecasting motion trajectories of elbow and knee joints during infant crawling based on long–short-term memory (LSTM) networks by Jieyi Mo, Qiliang Xiong, Ying Chen, Yuan Liu, Xiaoying Wu, Nong Xiao, Wensheng Hou

“…We partitioned the data set into 70% for training and 30% for testing to evaluate predictive performance. …”
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Structural integrity and hybrid ANFIS-PSO modeling of the corrosion rate of ductile irons in different environments by Ukoba K., Akinribide O.J., Adeleke O.

“…The experimental results from this study were used to validate a model generated from hybrid adaptive neuro-fuzzy inferences system-particle swarm optimization (ANFIS-PSO) algorithms. The hybrid ANFIS-PSO modelling technique was improvised for a detailed evaluation of corrosion rate of ductile cast iron materials in different environments. …”
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Navigating Samarinda's climate: A comparative analysis of rainfall forecasting models by Mislan, Andrea Tri Rian Dani

“…Data is divided into training and testing with a proportion of 90:10. Evaluation of goodness-of-fit using Root Mean Squared Error Prediction (RMSEP). …”
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Predictors of evacuation behavior: dataset on respondents’ route choice and web interaction by Dajana Snopková, Martin Tancoš, Lukáš Herman, Vojtěch Juřík

“…Abstract Empirical data on human evacuation behavior are invaluable for adjusting and training computational algorithms that simulate evacuation processes, including agent-based modeling. …”
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The intersection of AI and learning analytics: Enhancing institutional performance by Thabisa Maqoqa

“…Within the framework of a positivist paradigm, it was found that the introduction of AI has fostered the development of robust evaluation and assessment techniques, leading to increased faculty engagement. …”
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Accurate prediction of mediolateral episiotomy risk during labor: development and verification of an artificial intelligence model by Tingting Hu, Liheng Zhao, Xueling Zhao, Lin He, Xiaoli Zhong, Zhe Yin, Junjie Chen, Yanting Han, Ka Li

“…Abstract Objective The study developed an intelligent online evaluation system for mediolateral episiotomy, which incorporated machine learning algorithms and integrated maternal physiological data collected during delivery. …”
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Development of an interpretable model for foot soft tissue stiffness based on gait plantar pressure analysis by Xiaotian Bai, Xiao Hou, Dazhi Lv, Dazhi Lv, Jialin Wei, Jialin Wei, Yiling Song, Zhengyan Tang, Hongfeng Huo, Hongfeng Huo, Jingmin Liu

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