An Analysis of the Optimal Allocation of Core Human Resources in Family Enterprises Based on the Markov Model by Jinyang Cao

“…Compared with other model algorithms, the Markov model algorithm has the highest accuracy in predicting the state, and the accurate prediction results make the recruitment work predictable. …”
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Cross-Brand Machine Learning of Coffee’s Temporal Liking from Temporal Dominance of Sensations Curves by Hiroharu Natsume, Shogo Okamoto

“…The average prediction error across all brands was approximately 10% of the maximum instantaneous liking scores, and the mean correlation coefficients between the observed and predicted temporal scores ranged from 0.79 to 0.85 across the four brands, demonstrating the model’s potential for cross-brand prediction. …”
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Application of ensemble learning techniques to model the atmospheric concentration of SO2 by A. Masih

“…In view of pollution prediction modeling, the study adopts homogenous (random forest, bagging, and additive regression) and heterogeneous (voting) ensemble classifiers to predict the atmospheric concentration of Sulphur dioxide. …”
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Personalized Music Recommendation Simulation Based on Improved Collaborative Filtering Algorithm by Hui Ning, Qian Li

“…On the basis of traditional recommendation technology, in view of the characteristics of the context information in music recommendation, a personalized and personalized music based on popularity prediction is proposed. Recommended algorithm is MRAPP (Media Recommendation Algorithm based on Popularity Prediction). …”
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Spectrophotometric and Multivariate Calibration Techniques for Simultaneous Determination of Different Drugs in Pharmaceutical Formulations and Human Urine: Evaluation of Greenness... by Ahmed Mostafa

“…External validation data set composed of seven mixtures was used, and different figures of merits such as root mean square error of prediction, standard error of prediction, bias, and relative error of prediction were calculated, and satisfactory results were obtained. …”
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Comparison of artificial neural network models of categorized daily electric load by Vildan Evren, İlker Ali Ozkan

“…Load estimation is based on predicting future electric load by examining past conditions. …”
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Alternating current servo motor and programmable logic controller coupled with a pipe cutting machine based on human-machine interface using dandelion optimizer algorithm - attenti... by Santosh Prabhakar Agnihotri, Mandar Padmakar Joshi

“…Recognizing the existing limitations in parameter optimization and system behavior prediction, a novel hybrid approach is introduced. The methodology combines a Dandelion optimizer algorithm (DOA) for servo motor parameter optimization and an Attention pyramid convolution neural network (APCNN) (APCNN) for system behavior prediction. …”
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AiGPro: a multi-tasks model for profiling of GPCRs for agonist and antagonist by Rahul Brahma, Sunghyun Moon, Jae-Min Shin, Kwang-Hwi Cho

“…Each prediction is further accompanied by a confidence score, offering a quantitative measure of activity likelihood. …”
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Perbandingan Algoritme Machine Learning untuk Memprediksi Pengambil Matakuliah by Fitra A. Bachtiar, Indra K. Syahputra, Satrio A. Wicaksono

“…Thus, there is a need to build a system that can predict students taking courses. However, there are many algorithms that can be used for the prediction. …”
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Real-Time Visualization Optimization Management Simulation of Big Data Stream on Industrial Heritage Cloud Platform by Mengya Gao

“…This paper proposes a real-time visualization optimization management simulation of an industrial heritage cloud platform, which realizes the high reliability and diversified storage and utilization of industrial big data by the cloud data distributed storage subsystem. The big data prediction model of the GRU neural network based on a spark distributed framework is constructed to realize the prediction of industrial genetic data. …”
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Multi-scale fracture characterization method for transitional shale reservoir based on post-stack multi-attribute ant-tracking fusion and pre-stack wide-azimuth gathers AVAZ analys... by Hongjie Peng, Jingtao Zhao, Zhen Qiu, Qin Zhang, Wen Liu, Weiliang Kong, Wanli Gao, Tongjie Sheng, Wenyu Li, Yugang Yang

“…The results of the fracture prediction are analyzed and validated. A novel and reliable methodology, designed specifically for the challenges of transitional shale reservoirs, has been developed for combined pre-stack and post-stack seismic multi-scale fracture prediction. …”
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The Advantage of Using International Multimodel Ensemble for Seasonal Precipitation Forecast over Israel by Amir Givati, Mashor Housh, Yoav Levi, Dror Paz, Itzhak Carmona, Emily Becker

“…Moreover, prediction with larger number of models in the ensemble produces more robust predictions. …”
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The Development of a Hybrid EnKF-3DVAR Algorithm for Storm-Scale Data Assimilation by Jidong Gao, Ming Xue, David J. Stensrud

“…A hybrid 3DVAR-EnKF data assimilation algorithm is developed based on 3DVAR and ensemble Kalman filter (EnKF) programs within the Advanced Regional Prediction System (ARPS). The hybrid algorithm uses the extended alpha control variable approach to combine the static and ensemble-derived flow-dependent forecast error covariances. …”
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Evaluating Lateral Spreading Using Newmark Method Based on Liquefaction Triggering by Yanxin Yang, Junhua Chen, Zhenqiang Zhang, Jianlin Ma

“…The prediction of liquefaction-induced lateral spreading is an important geotechnical engineering problem. …”
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Comparison of Two Toric IOL Calculation Methods by C. Kern, K. Kortüm, M. Müller, A. Kampik, S. Priglinger, W. J. Mayer

“…Prediction error, median absolute error, and refractive astigmatism error were evaluated for the standard calculator. …”
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Analysis of Noise Pollution during Dussehra Festival in Bhubaneswar Smart City in India: A Study Using Machine Intelligence Models by Sourav Kumar Bhoi, Chittaranjan Mallick, Chitta Ranjan Mohanty, Ranjan Soumya Nayak

“…In this work, the noise pollution level of Bhubaneswar smart city during Dussehra 2020 is predicted using different supervised machine learning (ML) prediction models. …”
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Evaluation of the Risk of Recurrence in Patients with Local Advanced Rectal Tumours by Different Radiomic Analysis Approaches by Alaa Khadidos, Adil Khadidos, Olfat M. Mirza, Tawfiq Hasanin, Wegayehu Enbeyle, Abdulsattar Abdullah Hamad

“…These potential applications can be grouped into several categories like evaluation of the reproducibility of texture data, prediction of response to treatment, prediction of the occurrence of metastases, and prediction of survival. …”
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Monitoring Population Phenology of Asian Citrus Psyllid Using Deep Learning by Maria Bibi, Muhammad Kashif Hanif, Muhammad Umer Sarwar, Muhammad Irfan Khan, Shouket Zaman Khan, Casper Shikali Shivachi, Asad Anees

“…In comparison with other regression techniques, a deep neural network-based prediction model resulted in the least root mean squared error values while predicting egg, nymph, and adult populations.…”
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Shallow Foundation Settlement Quantification: Application of Hybridized Adaptive Neuro-Fuzzy Inference System Model by Mariamme Mohammed, Ahmad Sharafati, Nadhir Al-Ansari, Zaher Mundher Yaseen

“…Results indicated ANFIS-PSO model exhibited an accurate and reliable prediction data intelligent and had the highest predictability performance against all employed models. …”
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Systematic Research on the Application of Steel Slag Resources under the Background of Big Data by Le Kang, Hui Ling Du, Hao Zhang, Wan Li Ma

“…Secondly, the steel slag prediction model based on the convolution neural network (CNN) is established. …”
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