A comparative study of the performance of ten metaheuristic algorithms for parameter estimation of solar photovoltaic models by Adel Zga, Farouq Zitouni, Saad Harous, Karam Sallam, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

“…This estimation is challenging due to computational complexity and the risk of optimization errors, which can hinder reliable performance predictions. The algorithms evaluated include the Crayfish Optimization Algorithm, the Golf Optimization Algorithm, the Coati Optimization Algorithm, the Crested Porcupine Optimizer, the Growth Optimizer, the Artificial Protozoa Optimizer, the Secretary Bird Optimization Algorithm, the Mother Optimization Algorithm, the Election Optimizer Algorithm, and the Technical and Vocational Education and Training-Based Optimizer. …”
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Algorithm of athletes’ fitness structure individual features’ determination with the help of multidimensional analysis (on example of basketball) by Zh.L. Kozina, M. Cieslicka, K. Prusik, R. Muszkieta, I.N. Sobko, O.A. Ryepko, T.A. Bazilyuk, S.B. Polishchuk, A.V. Osiptsov, S.A. Korol

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Assessment of flood vulnerability in a coastal metropolitan city for sustainable environmental using machine learning methods by Rana Alabdan, C. Sharmila, Nuha Alruwais, Haya Mesfer Alshahrani, S. Anbukkarasi, M. Sujatha, S. Vivek

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Prediction Approaches for Smart Cultivation: A Comparative Study by Amitabha Chakrabarty, Nafees Mansoor, Muhammad Irfan Uddin, Mosleh Hmoud Al-adaileh, Nizar Alsharif, Fawaz Waselallah Alsaade

“…Other contemporary machine learning algorithms, namely, support vector machine, random forest, and logistic regression, have average prediction accuracy of around 68.9%, 91.2%, and 62.39%, respectively.…”
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A Novel Multi-Level Perceptron for Accurate Heart Stroke Diagnosis by Muhammad Zaman, Muhammad Khubaib, Tanzila Kahkashan, Anam Zahoor, Narges Shahbaz, Shahzad Shoukat, Fahma Nisar

“…Different types of Machine Learning and deep learning algorithms are used for heart stroke predictions. In this paper we purposed Novel Multi Layer-Perceptron (MLP) that are efficient in classification and in heart stoke prediction that model achieve high accuracy of 99%.…”
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Applying machine learning to predict bowel preparation adequacy in elderly patients for colonoscopy: development and validation of a web-based prediction tool by Jianying Liu, Wei Jiang, Yahong Yu, Jiali Gong, Guie Chen, Yuxing Yang, Chao Wang, Dalong Sun, Xuefeng Lu

“…In external validation, the SVM model maintained robust performance with an AUC of 0.889. The SHAP algorithm further explained the contribution of each feature to model predictions.Conclusion The study developed an interpretable and practical machine learning model for predicting bowel preparation adequacy in elderly patients, facilitating early interventions to improve outcomes and reduce resource wastage.…”
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Application of radiomics-based prediction model to predict preoperative lymph node metastasis in prostate cancer: a systematic review and meta-analysis by Yanghuang Zheng, Yuelin Du, Biao Zhang, Helin Zhang, Panfeng Shang, Zizhen Hou

“…The subgroup analysis showed that the least absolute shrinkage and selection operator regression algorithm had the higher diagnostic sensitivity, with a pooled sensitivity of 0.96 (95% CI [0.90 - 1.00]) (p = 0.02), while the random forest algorithm was the opposite, with a pooled sensitivity of 0.48 (95% CI [0.16 - 0.80]) (p = 0.01). …”
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Enhancing LoRaWAN Performance Using Boosting Machine Learning Algorithms Under Environmental Variations by Maram A. Alkhayyal, Almetwally M. Mostafa

“…The findings show that boosting algorithms, particularly LightGBM, are highly effective for path loss prediction in LoRaWANs.…”
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Improving Random Forest Algorithm for University Academic Affairs Management System Platform Construction by Jinyang Dai

“…In view of the complexity, heterogeneity, and security of college educational administration data and the difficulty of predicting and analyzing college students’ achievements, this paper designs a college educational administration management system platform based on improved random forest algorithm. …”
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Research on scraper conveyor load prediction method based on wavelet transform and BP neural network by Dan Zhang, Jiafeng Qin, Weidong Wu, Yongtao Zhu, Weijie Guo

“…By studying the mapping relationship between motor load and current based on the BP neural network algorithm, and taking the scraper conveyor current as the input condition, wavelet decomposition and data reconstruction of historical current data are carried out, and time series prediction is performed on the original data samples and reconstructed data samples, respectively. …”
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Online English Teaching Course Score Analysis Based on Decision Tree Mining Algorithm by Xiaojun Jiang

“…In this paper, we use the global search advantage of genetic algorithm to build a GABP hybrid prediction model to solve the local minimum problem of BP neural network algorithm. …”
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Online English teaching resource recommendation method design based on LightGCNCSCM by Jing Tang

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Empowering digital self-determination by Christian Filk

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Development of a cataract screening model using an open dataset and deep machine learning algorithms by S.N. Sakhnov, K.D. Axenov, L.E. Axenova, V.V. Vronskaya, A.O. Martsinkevich, V.V. Myasnikova

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Optimized SVR with nature-inspired algorithms for environmental modelling of mycotoxins in food virtual-water samples by Abdullahi G. Usman, Sagiru Mati, Hanita Daud, Ahmad Abubakar Suleiman, Sani I. Abba, Hijaz Ahmad, Taha Radwan

“…This study proposed the use of a support vector regression (SVR) predictive model improved by two metaheuristic algorithms used for optimization namely, Harris Hawks Optimization (HHO) and Particle Swarm Optimization (PSO) to predict chromatographic retention time of various food mycotoxin groups. …”
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Identification of early prognostic biomarkers in Severe Fever with Thrombocytopenia Syndrome using machine learning algorithms by Jie Zhu, Jianmei Zhou, Chunhui Tao, Guomei Xia, Bingyan Liu, Xiaowei Zheng, Xu Li, Zhenhua Zhang

“…Decision Curve Analysis indicated a good balance between model benefits and risks.Conclusions a-HBDH and its change slope along with central nervous symptom manifestations within 7-10 days after onset accurately predicted mortality in SFTS. Various algorithms provided a comprehensive overview of disease progression and constructed more stable and efficient models.…”
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Optimization of SVM Parameters with Hybrid CS-PSO Algorithms for Parkinson’s Disease in LabVIEW Environment by Duygu Kaya

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Meta-heuristics meet sports: a systematic review from the viewpoint of nature inspired algorithms by Ariyaratne M.K.A., Silva R.M.

“…The necessity of sophisticated algorithms to investigate different NP hard problems encountered in sports analytics was established in the recent past. …”
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Prognostic Models Using Machine Learning Algorithms and Treatment Outcomes of Papillary Thyroid Carcinoma Variants by Sakhr Alshwayyat, Haya Kamal, Owais Ghammaz, Tala Abdulsalam Alshwayyat, Mustafa Alshwayyat, Ramez M. Odat, Hamdah Hanifa, Wafa Asha, Nesreen A. Saadeh

“…Methods Chi‐square tests, Kaplan–Meier curves, log‐rank tests, and Cox regression were used. Five ML algorithms constructed prognostic models predicting 5‐year survival, validated using the AUC of the ROC curve. …”
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Assessment of hydrological loading displacement from GNSS and GRACE data using deep learning algorithms by Changshou Wei, Maosheng Zhou, Zhixing Du, Lijing Han, Hao Gao

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