The Prediction of Sports Economic Development Prospect in Different Regions by Improved Artificial Bee Colony Algorithm by Lei Liu, Guangda Song

“…Therefore, the improved artificial bee colony algorithm can best predict the development of the sports economy in different regions, and its accuracy, periodicity, and calculation time are better than those of the original artificial bee colony algorithm.…”
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Research on Prediction model of Carotid‐Femoral Pulse Wave Velocity: Based on Machine Learning Algorithm by Minghui Chen, Jing Xiong, Moran Li, Tao Hu, Yi Zhang

“…It is feasible to use a machine learning algorithm based on baPWV and other readily available clinical parameters to predict cf‐PWV.…”
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Application of Immunological and Swarm Intelligence Learning-Based Algorithm for Industrial Grade Computer Sales Prediction by Zhen-Yao Chen

“…The algorithm then evaluates results from five standard inspections and an empirical industrial grade computer (IgC) sales prediction instance in Taiwan, which reveals that the proposed SAIPS algorithm exceeds the performance among related algorithms as well as the relevant auto-regressive integrated moving average (ARIMA) models in terms of accuracy and time spent.…”
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Prediction of strength parameters of concrete containing different additives using optimized neural network algorithm by Behzad Haseli, Gholamreza Nouri, Meysam Mardi, Ehsan Adili, Mohammad Bahari

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Ensemble machine learning algorithm for anti-VEGF treatment efficacy prediction in diabetic macular edema by Yu Fang, Jianwei Lin, Peiwen Xie, Huishan Zhu, Tsz Kin Ng, Guihua Zhang

“…Conclusion This study established an ensemble ML algorithm based on 3D-OCT images and clinical features for automatic detection of treatment responses to anti-VEGF treatment in DME patients to predict the efficacy of anti-VEGF treatment in DME patients and assist clinicians in optimal treatment decisions.…”
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Development and validation of a deep learning algorithm for prediction of pediatric recurrent intussusception in ultrasound images and radiographs by Yu-feng Qian, Wan-liang Guo

“…Conclusions Deep learning algorithms developed using multimodal medical imaging may help predict recurrent intussusception. …”
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Performance Enhancement of a Grid Connected Wind Turbine-Based PMSG Using Effective Predictive Control Algorithm by Mahmoud A. Mossa, Rasha A. Mohamed, Ameena Saad Al-Sumaiti

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Energy Consumption Prediction in Iran: A Hybrid Machine Learning and Genetic Algorithm Method with Sustainable Development Considerations by Seyyed Mohammad Mehdi Fatemi Bushehri, Saeed Dehghan Khavari, Seyed Hossein Mirjalili, Hamid Babaei Meybodi, Mohsen Sardari Zarchi

“…The algorithm was able to select 14 features as the most effective indicators in predicting energy consumption from all the 104 ones in the IREC with 500 repetitions. …”
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Application of machine learning algorithms in predicting new onset hypertension: a study based on the China Health and Nutrition Survey by Manhui Zhang, Xian Xia, Qiqi Wang, Yue Pan, Guanyi Zhang, Zhigang Wang

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Enhanced AdaBoostM1 with Multilayer Perceptron for Stock Price Prediction by Rebwar Mala Nabi, Soran AB. Saeed, Habibollah Haron

Subjects: “…Stock Market Price Prediction…”
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Predicting failures in fiber optic information transmission systems with support of machine learning by Nafisa Juraeva, Dilmurod Davronbekov, Ulugbek Turdiev

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Cooling Load Prediction via Support Vector Regression in Individual and Hybrid Approaches by Honglei Yao, Andrew Topper

“…Moreover, the hybrid SVCS model, with its minimal RMSE value of 0.747 and remarkable R2 value of 0.994, consistently yields reliable results for CL prediction. This study advances the field of energy-efficient building management by demonstrating how machine learning methods and clever optimization algorithms can be used to predict cooling loads accurately.…”
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Machine Learning and Deep Learning Models for Dengue Diagnosis Prediction: A Systematic Review by Daniel Cristobal Andrade Girón, William Joel Marín Rodriguez, Flor de María Lioo-Jordan, Jose Luis Ausejo Sánchez

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Machine learning predictions on the output parameters of common rail direct injection engines fueled with ternary blend by Subramanian Karthikeyan, Paramasivam Sathiyagnanam Amudhavalli, Dillikannan Damodharan

“…This study aims to employ a machine learning algorithm (MLA) to predict Common Rail Direct Injection (CRDI) engine emissions and performance using alternative feedstock. …”
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Comparative Study on Hyperparameter Tuning for Predicting Concrete Compressive Strength by Jeonghyun Kim, Donwoo Lee

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A study on the effectiveness of machine learning models for hepatitis prediction by Popy Khatun, Shafeel Umam, Rubaiya Binte Razzak, Iffat Binta Shamsuddin, Nahid Salma

“…This study seeks to address this gap by applying a range of advanced machine learning (ML) algorithms to predict hepatitis, contributing to global efforts to enhance public health outcomes. …”
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Optimization of Markov chain modeling in predicting college student retention by Kien Nguyen

“…This study presents a rigorous algorithm, coupled with a prediction model, capable of selecting parameters that provide the most accurate results for term-to-term retention prediction using the Markov chain analysis. …”
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Self-adaptive prediction and prewarning model of mine gas concentration by Dingwen Dong

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Ensemble prediction modeling of flotation recovery based on machine learning by Guichun He, Mengfei Liu, Hongyu Zhao, Kaiqi Huang

“…First, the outliers are processed using the box chart method and filtering algorithm. Then, the decision tree (DT), support vector regression (SVR), random forest (RF), and the bagging, boosting, and stacking integration algorithms are employed to construct a flotation recovery prediction model. …”
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Advancing Knowledge on Machine Learning Algorithms for Predicting Childhood Vaccination Defaulters in Ghana: A Comparative Performance Analysis by Eliezer Ofori Odei-Lartey, Stephaney Gyaase, Dominic Asamoah, Thomas Gyan, Kwaku Poku Asante, Michael Asante

“…This study evaluated the utility of machine learning algorithms for predicting childhood vaccination defaulters in Ghana, addressing the limitations of traditional statistical methods when handling complex, high-dimensional health data. …”
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