An ideally designed deep trust network model for heart disease prediction based on seagull optimization and Ruzzo Tompa algorithm by Yuan Jin, Yunliang Lai, Azadeh Noori Hoshyar, Nisreen Innab, Meshal Shutaywi, Wejdan Deebani, A. Swathi

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Estimating Daily Reference Crop Evapotranspiration in Northeast China Using Optimized Empirical Models Based on Heuristic Intelligence Algorithms by Zongyang Li, Zhengxin Zhao, Liwen Xing, Lu Zhao, Ningbo Cui, Huanjie Cai

“…In this research, meteorological data from 30 sites in Northeast China over the past 59 years (1961–2019) were selected to evaluate the simulation accuracy of 11 ETo estimation models. By using the least square method (LSM) and three population heuristic intelligent algorithms—a genetic algorithm (GA), a particle swarm optimization algorithm (PSO), and a differential evolution algorithm (DE)—the parameters of eleven kinds of models were optimized, respectively, and the ETo estimation model suitable for northeast China was selected. …”
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Proposed improvement of product support packaging material defects using the Cross-Industry Standard Process for Data Mining (CRISP-DM) approach by Rina Fitriana, Anik Nur Habyba, Gina Almas Nabiha, Sannia Mareta

“…The Data Preparation stage performs data cleaning, integration, transformation, and preprocessing. The Modelling stage makes classification with C4.5 and the Cart decision tree algorithm. …”
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Lateral Control of Autonomous Vehicles with Data Dropout via an Enhanced Data-driven Model-free Adaptive Control Algorithm by Shida Liu, Yuhao Yan, Honghai Ji, Li Wang

“…Addressing the lateral path tracking control issue of autonomous vehicles during data dropout, an improved model-free adaptive control system with data compensation (DC-EMFAC) is introduced. …”
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A Genetic algorithm aided hyper parameter optimization based ensemble model for respiratory disease prediction with Explainable AI. by Balraj Preet Kaur, Harpreet Singh, Rahul Hans, Sanjeev Kumar Sharma, Chetna Sharma, Md Mehedi Hassan

“…Motivated by the above, in this proposal, we design an improved model to predict the existence of respiratory disease among patients by incorporating hyperparameter optimization and feature selection. …”
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Predictive Modeling of Yoga's Impact on Venous Clinical Severity Scoring Using Gaussian Process Classification and Advanced Optimization Algorithms by Yazdan Ashgevari, Faranak Kazemi

“…For the VCSS.3 target, the precision accuracy improved to 0.909, 0.882, and 0.821 for the GPC, GPAO, and GPMG models, respectively. …”
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An Overview of Remaining Useful Life Prediction of Battery Using Deep Learning and Ensemble Learning Algorithms on Data-Dependent Models by Sravanthi C. L., Chandra Sekhar J. N., N. Chinna Alluraiah, Dhanamjayulu C., Harish Kumar Pujari, Baseem Khan

“…This article classifies and summarises the RUL prediction by data-dependent models using machine learning (ML), deep learning (DL) and ensemble learning (EL) algorithms suggested in a last few years. …”
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Developing a Machine Learning-Driven Model that Leverages Meta-Heuristic Algorithms to Forecast the Load-Bearing Capacity of Piles by Tianhua Zhou

“…This study used the Gaussian Process Regression (GPR) model as a problem-solving method for building a machine-learning model. …”
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SKGRec: A Semantic-Enhanced Knowledge Graph Fusion Recommendation Algorithm with Multi-Hop Reasoning and User Behavior Modeling by Siqi Xu, Ziqian Yang, Jing Xu, Ping Feng

“…In addition, a multi-hop relational path inference mechanism is introduced to capture long-distance dependencies to improve the depth of user interest modeling. Experiments on the Amazon-Book and Last-FM datasets show that SKGRec significantly outperforms several state-of-the-art recommendation algorithms on the Recall@20 and NDCG@20 metrics. …”
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Identification of right ventricular dysfunction with LogNNet based diagnostic model: A comparative study with supervised ML algorithms by Mehmet Tahir Huyut, Andrei Velichko, Maksim Belyaev, Yuriy Izotov, Şebnem Karaoğlanoğlu, Bünyamin Sertoğullarından, Sıddık Keskin, Dmitry Korzun

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Forecasting the daily evaporation by coupling the ensemble deep learning models with meta-heuristic algorithms and data pre-processing in dryland by Tonglin Fu, Dong Wang, Jing Jin

“…Specifically, integrating meta-heuristic algorithms, ensemble deep learning models, and data preprocessing techniques for evaporation prediction is notably scarce. …”
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Risk Assessment and Spatial Zoning of Rainstorm and Flood Hazards in Mountainous Cities Using the Random Forest Algorithm and the SCS Model by Zixin Xie, Bo Shu

“…Through the Random Forest (RF) algorithm and the Soil Conservation Service (SCS) model, this study aimed to assess and demarcate rainstorm and flood hazard risks in Huangshan City. …”
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Machine learning algorithms for diabetic kidney disease risk predictive model of Chinese patients with type 2 diabetes mellitus by Lu-Xi Zou, Xue Wang, Zhi-Li Hou, Ling Sun, Jiang-Tao Lu

“…Among the seven forecasting models constructed by MLAs, the accuracy of the Light Gradient Boosting Machine (LightGBM) model was the highest, indicated that the LightGBM algorithms might perform the best for predicting 3-year risk of DKD onset.Conclusions Our study could provide powerful tools for early DKD risk prediction, which might help optimize intervention strategies and improve the renal prognosis in T2DM patients.…”
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A Novel Framework for Improving Soil Organic Carbon Mapping Accuracy by Mining Temporal Features of Time-Series Sentinel-1 Data by Zhibo Cui, Bifeng Hu, Songchao Chen, Nan Wang, Defang Luo, Jie Peng

“…The data volume was reduced by 73.27% relative to the initial time-series dataset when the optimal monitoring period was determined. (2) Introducing time-series S-1 data into SOC mapping significantly improved CNN-LSTM model performance (R² = 0.80, RPD = 2.24, RMSE = 1.11 g kg⁻¹). …”
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Variogram modelling optimisation using genetic algorithm and machine learning linear regression: application for Sequential Gaussian Simulations mapping by André William Boroh, Alpha Baster Kenfack Fokem, Martin Luther Mfenjou, Firmin Dimitry Hamat, Fritz Mbounja Besseme

“…The objective of this study is to develop an advanced approach to variogram modelling by integrating genetic algorithms (GA) with machine learning-based linear regression, aiming to improve the accuracy and efficiency of geostatistical analysis, particularly in mineral exploration. …”
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Genetic programming-based algorithms application in modeling the compressive strength of steel fiber-reinforced concrete exposed to elevated temperatures by Mohsin Ali, Li Chen, Qadir Bux Alias Imran Latif Qureshi, Deema Mohammed Alsekait, Adil Khan, Kiran Arif, Muhammad Luqman, Diaa Salama Abd Elminaam, Amir Hamza, Majid Khan

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Two-step hybrid model for monthly runoff prediction utilizing integrated machine learning algorithms and dual signal decompositions by Shujun Wu, Zengchuan Dong, Sandra M. Guzmán, Gregory Conde, Wenzhuo Wang, Shengnan Zhu, Yiqing Shao, Jinyu Meng

“…This study introduces an innovative two-step hybrid runoff prediction framework tailored for the headwater region of the Yellow River Basin (YRB) to improve prediction accuracy and elucidate the runoff modeling process. …”
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Voxelwise characterization of noise for a clinical photon-counting CT scanner with a model-based iterative reconstruction algorithm by Luigi Masturzo, Patrizio Barca, Luca De Masi, Daniela Marfisi, Antonio Traino, Filippo Cademartiri, Marco Giannelli

“…Photon-counting detector technology has the capability to appreciably reduce CT imaging noise and improve spatial uniformity of noise values. In photon-counting CT, a model-based iterative reconstruction algorithm (QIR) allows decreasing effectively image noise. …”
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Mechanism-learning prediction model for pitting depth of buried pipeline based on HMOGWO-RF by Fulin SONG, Hong ZHAO, Xingyuan MIAO

“…The resulting feature subsets, which are both representative and optimized for performance, contribute to improvements in model stability and prediction accuracy. …”
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Multi-constraint smart UAV healthcare transportation path using imperial competition algorithm for smart cities by Haewon Byeon, Janjhyam Venkata Naga Ramesh, Azzah AlGhamdi, Mukesh Soni, Divya Nimma, Sridevi Pothumarthi, Mohammad Shabaz

“…This algorithm introduces a sine disturbance strategy and adds Imperial Reform stages to improve the search accuracy of the algorithm. …”
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