A Study on the Establishment of a Variable Stiffness Physical Model of Abdominal Soft Tissue and an Interactive Massage Force Prediction Algorithm by Xinyi Tang, Ping Shi, Zhenjie Luo, Sujiao Li, Hongliu Yu

“…Furthermore, a transformer-based machine learning algorithm was developed. This algorithm predicts interaction forces using anthropometric and physiological characteristics. …”
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A Prediction Method for Floor Water Inrush Based on Chaotic Fruit Fly Optimization Algorithm–Generalized Regression Neural Network by Zhijie Zhu, Chen Sun, Xicai Gao, Zhuang Liang

“…To this end, a prediction method for floor water inrush combining the chaotic fruit fly optimization algorithm (CFOA) and the generalized regression neural network (GRNN) is proposed. …”
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Long-term prediction of wind speed in La Serena City (Chile) using hybrid neural network-particle swarm algorithm by Juan A Lazzús, Ignacio Salfate

“…In order to obtain a more effective correlation and prediction, a particle swarm algorithm was implemented to update the weights of the network. 43800 data points of wind speed were used (years 2003- 2007), and the past values of wind speed, relative humidity, and air temperature were used as input parameters, considering that these meteorogical parameters are more readily available around the globe. …”
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Development and validation of a risk prediction model for kinesiophobia in postoperative lung cancer patients: an interpretable machine learning algorithm study by Chuang Li, Youbei Lin, Xuyang Xiao, Xinru Guo, Jinrui Fei, Yanyan Lu, Junling Zhao, Lan Zhang

“…This study demonstrates that machine learning models—particularly the RF algorithm—hold substantial promise for predicting kinesiophobia in postoperative lung cancer patients. …”
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A Risk Prediction Model (CMC-AKIX) for Postoperative Acute Kidney Injury Using Machine Learning: Algorithm Development and Validation by Ji Won Min, Jae-Hong Min, Se-Hyun Chang, Byung Ha Chung, Eun Sil Koh, Young Soo Kim, Hyung Wook Kim, Tae Hyun Ban, Seok Joon Shin, In Young Choi, Hye Eun Yoon

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Poster #19 - Influence of meteorological factors on influenza in a warm temperate to subtropical transitional zone and predictions based on an LSTM algorithm by Nadia Nisar, Nazish Badar, Inayah Safdar, Muhammad Salman

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Using Sono-Electro-Persulfate Process for Atenolol Removal from Aqueous Solutions: Prediction and Optimization with the ANFIS Model and Genetic Algorithm by Nasrin Zahedi, Bahare Dehdashti, Farzaneh Mohammadi, Maryam Razaghi, Zeynab Moradmand, Mohammad Mehdi Amin

“…Finally, an adaptive neuro-fuzzy inference system (ANFIS) with 99.63% accuracy and a genetic algorithm (GA) were used to analyze and interpret data and predict optimal conditions. …”
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LPBSA: Pre-clinical data analysis using advanced machine learning models for disease prediction by Dana R. Hamad, Tarik A. Rashid

“…The current study introduces an optimization algorithm, Learner Performance-Based Behavior with Simulated Annealing (LPBSA), integrated with Multilayer Perceptron (MLP) as a neural network technique to improve disease prediction accuracy. …”
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Noninvasive Blood Glucose Level Monitoring for Predicting Insulin Infusion Rate Using Multivariate Data by G. Geetha, J. Godwin Ponsam, K. Nimala

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A Random Forest-Based Predictive Model for Student Academic Performance: A Case Study in Indonesian Public High Schools by Rifa Andriani Saputri, Asrianda Asrianda, Lidya Rosnita

“…The rapid advancement of information technology has transformed education by providing tools to accurately predict students' academic performance. …”
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Enhancing Long-Term Flood Forecasting with SageFormer: A Cascaded Dimensionality Reduction Approach Based on Satellite-Derived Data by Fatemeh Ghobadi, Amir Saman Tayerani Charmchi, Doosun Kang

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Research on Slope Stability Prediction Based on MC-BKA-MLP Mixed Model by Yan Lu, Hongze Zhao

“…Subsequently, a novel Black Kite Algorithm (BKA) was developed to enhance the prediction model of a multilevel perceptron neural network. …”
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Predicting Coronary Heart Disease Using Data Mining and Machine Learning Solutions by VIJAI M. MOORTHY, BHUPAL N. DHARAMSOTH, VIJAYALAKSHMI MUTHUKARUPPAN, ARUL ELANGO, KALAIARASI GANESAN

“…The true positive rate for the GB algorithm’s predictions of patients was 98.3%. The study hypothesizes that the GB method predicts the Framingham dataset better than other algorithms using 4240 samples.…”
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Enhanced LSTM-based AI model for accurate dissolved oxygen prediction in aquaculture systems by Ala Saleh Alluhaidan, Prabu P, Romana Aziz, Shakila Basheer

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Tropical Cyclones Across Global Basins: Dynamics, Tracking Algorithms, Forecasting, and Emerging Scientometric Research Trends by Vivek Singh, Gaurav Tiwari, Amarendra Singh, Rajeeb Samanta, Atul Kumar Srivastava, Deewan Singh Bisht, Ashish Routray, Sushil Kumar, Shivaji Singh Patel, Abhishek Lodh

“…Notably, research since 2019 highlights a shift toward machine‐based algorithms aimed at improving intensity predictions. …”
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Large-scale terminal access algorithm based on slot ALOHA and adaptive access class barring by Zhenyu ZHU, Xiaorong ZHU, Yan CAI, Hongbo ZHU

“…In order to solve the problem of high collision rate and low timeliness of large-scale terminals access in the Internet of things, a large-scale terminal access algorithm based on slot ALOHA and adaptive access class barring (ACB) was proposed.Firstly, the services were classified based on the data from each terminal by the volume of the services processed and the requirements for delay.For the services that were not time-sensitive and whose effective data portion was less than 1 000 bit, a slot-based ALOHA-based competitive access method was used.ACB-based random access was used for the services that were time-sensitive or whose data portion was greater than 1 000 bit.On this basis, a method was proposed for predicting the access application volume based on the quantitative estimation, and dynamically adjusting the ACB control parameters based on this predicted value.Simulation results show that compared with other existing access algorithms, the proposed algorithm reduces the collision rate and improves the system access success rate under the premise of ensuring the high priority service delay requirements.…”
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A Noise Reduction Method for Signal Reconstruction and Error Compensation of a Maglev Gyroscope Under Persistent External Interference by Di Liu, Zhen Shi, Ziyi Yang, Chenxi Zou

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Factors influencing the acceptance and usage of ChatGPT as an emerging learning tool among higher education students in Bangladesh: a structural equation modeling by Md. Hasan Howlader, Mortuja Mahamud Tohan, Sayeeda Zaman, Sanjoy Kumar Chanda, Guo Jiaxin, Md. Ashfikur Rahman

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A Dual Filter Based on Radial Basis Function Neural Networks and Kalman Filters with Application to Numerical Wave Prediction Models by Athanasios Donas, Ioannis Kordatos, Alex Alexandridis, George Galanis, Ioannis Th. Famelis

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Deep Learning-Based Recurrence Prediction in HER2-Low Breast Cancer: Comparison of MRI-Alone, Clinicopathologic-Alone, and Combined Models by Seoyun Choi, Youngmi Lee, Minwoo Lee, Jung Hee Byon, Eun Jung Choi

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