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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Machine learning algorithms to predict heart failure with preserved ejection fraction among patients with premature myocardial infarction by Jing-xian Wang, Chang-ping Li, Zhuang Cui, Yan Liang, Yu-hang Wang, Yu Zhou, Yin Liu, Jing Gao, Jing Gao, Jing Gao, Jing Gao

“…This study aims to develop a model based on a machine learning algorithm that can predict the risk of in-hospital HFpEF in patients with PMI early and quickly.MethodsThis prospective study consecutively included PMI patients from January 2017 to December 2022. …”
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Enhanced Localization in Wireless Sensor Networks Using a Bat-Optimized Malicious Anchor Node Prediction Algorithm by Balachandran Nair Premakumari Sreeja, Gopikrishnan Sundaram, Marco Rivera, Patrick Wheeler

“…To address this challenge, we propose the security-aware localization using bat-optimized malicious anchor prediction (BO-MAP) algorithm. This approach utilizes a refined bat optimization algorithm to improve both the precision of localization and the security of WSNs. …”
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P336: Testing concordance of pathogenicity predictions from orthogonal machine learning algorithms and signal to noise analysis by Trevor Williams, Leonie Kurzlechner, Yuya Kobayashi, Keith Nykamp, Andrew Landstrom, Flavia M. Facio

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Development of an interpretable QSPR model to predict the octanol-water partition coefficient based on three artificial intelligence algorithms by Ao Yang, Shirui Sun, Lu Qi, Zong Yang Kong, Jaka Sunarso, Weifeng Shen

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Research on the Prediction Model of Wheel Set Failure Rate for Urban Rail Trains Based on IPSO-BP Algorithm by HE Deqiang, SUN Yi, MENG Jiwei, LIU Jianren

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Predicting the Feasibility of Phenol Extraction from Water in Different Solvents Using the NRTL Model and a Genetic Algorithm by Nardjess Bouneb, Mouna Talbi, Amani Elgouacem, Abir Mezen

“…The predicted results are in agreement with experimental phase equilibrium data. …”
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Reservoir water level prediction using combined CEEMDAN-FE and RUN-SVM-RBFNN machine learning algorithms by Lan-ting Zhou, Guan-lin Long, Can-can Hu, Kai Zhang

“…This study proposed a method for reservoir water level prediction based on CEEMDAN-FE and RUN-SVM-RBFNN algorithms. …”
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Robust-tuning machine learning algorithms for precise prediction of permeability impairment due to CaCO3 deposition by Mohammad Javad Khodabakhshi, Masoud Bijani, Masoud Hasani

“…Instead of creating new algorithms, the study focuses on refining existing ones to make them more effective for the field. …”
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Applying Machine Learning Algorithms for Spatial Modeling of Flood Susceptibility Prediction over São Paulo Sub-Region by Temitope Seun Oluwadare, Marina Pannunzio Ribeiro, Dongmei Chen, Masoud Babadi Ataabadi, Saba Hosseini Tabesh, Abiodun Esau Daomi

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A Linear Regression Prediction-Based Dynamic Multi-Objective Evolutionary Algorithm with Correlations of Pareto Front Points by Junxia Ma, Yongxuan Sang, Yaoli Xu, Bo Wang

“…Specifically, when the DMOP environment changes, this paper first constructs a spatio-temporal correlation model between various key points of the PF based on the linear regression algorithm; then, based on the constructed model, predicts a new location for each key point in the new environment; subsequently, constructs a sub-population by introducing the Gaussian noise into the predicted location to improve the generalization ability; and then, utilizes the idea of NSGA-II-B to construct another sub-population to further improve the population diversity; finally, combining the previous two sub-populations, re-initializing a new population to adapt to the new environment through a random replacement strategy. …”
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Cervical Cancer Prediction Based on Imbalanced Data Using Machine Learning Algorithms with a Variety of Sampling Methods by Mădălina Maria Muraru, Zsuzsa Simó, László Barna Iantovics

“…Data imbalance is frequent in healthcare data and has a negative influence on predictions made using ML algorithms. Cancer data, in general, and cervical cancer data, in particular, are frequently imbalanced. …”
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A Novel Approach for Blast-Induced Flyrock Prediction Based on Imperialist Competitive Algorithm and Artificial Neural Network by Aminaton Marto, Mohsen Hajihassani, Danial Jahed Armaghani, Edy Tonnizam Mohamad, Ahmad Mahir Makhtar

“…The scope of this study is to predict flyrock induced by blasting through a novel approach based on the combination of imperialist competitive algorithm (ICA) and artificial neural network (ANN). …”
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A novel strain-based bone-fracture healing algorithm is able to predict a range of healing outcomes by George T. Morgan, Lucas Low, Arul Ramasamy, Arul Ramasamy, Arul Ramasamy, Spyros D. Masouros

“…This study introduces a novel, strain-based fracture-healing algorithm designed to predict a wide range of healing outcomes, including both successful unions and non-unions. …”
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Soil Moisture Prediction Using Remote Sensing and Machine Learning Algorithms: A Review on Progress, Challenges, and Opportunities by Manoj Lamichhane, Sushant Mehan, Kyle R. Mankin

“…We reviewed the literature to extract and synthesize ML algorithms, reliable input features, and challenges in SM estimation using RS data. …”
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Early Yield Prediction of Oilseed Rape Using UAV-Based Hyperspectral Imaging Combined with Machine Learning Algorithms by Hongyan Zhu, Chengzhi Lin, Zhihao Dong, Jun-Li Xu, Yong He

“…The main results were as follows: (i) The yield prediction of oilseed rape using EWs showed better prediction and robustness compared to the full-spectral model. …”
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Predicting liver metastasis in pancreatic neuroendocrine tumors with an interpretable machine learning algorithm: a SEER-based study by Jinzhe Bi, Yaqun Yu

“…We applied 10 different machine learning algorithms to develop models for predicting the risk of liver metastasis in PaNETs patients. …”
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Energy Scheduling of Hydrogen Hybrid UAV Based on Model Predictive Control and Deep Deterministic Policy Gradient Algorithm by Haitao Li, Chenyu Wang, Shufu Yuan, Hui Zhu, Bo Li, Yuexin Liu, Li Sun

“…To overcome these limitations, this paper proposes a novel energy scheduling framework that integrates the Model Predictive Control (MPC) with a Deep Reinforcement Learning algorithm, specifically the Deep Deterministic Policy Gradient (DDPG). …”
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Presenting the AI models in predicting the settlement of earth dams using the results of spatiotemporal clustering and k-means algorithm by Behrang Beiranvand, Taher Rajaee, Mehdi Komasi

“…Therefore, the settlement location of the studied dam was determined using the results of the k-means clustering algorithm in the aforementioned AI models. The high accuracy of the results of the proposed method confirms the proper performance of using AI models in predicting and diagnosing the settlement of earthen dams using the results of k-means spatiotemporal clustering algorithm. …”
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Predicting the Temperature of a Permanent Magnet Synchronous Motor: A Comparative Study of Artificial Neural Network Algorithms by Nabil El Bazi, Nasr Guennouni, Mohcin Mekhfioui, Adil Goudzi, Ahmed Chebak, Mustapha Mabrouki

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