Average Corrosion Rate Prediction Model for Buried Oil and Gas Pipelines Based on SSA-LightGBM by Weigang Fu, Haitao Wang, Kuankuan Zhang, Xia Wang, Kunlun Chen, Chunmei Sun, Zhengwei Wang, Liuyang Song, Niannian Wang

“…Corrosion represents a major cause of damage and leakage in oil and gas pipelines, making accurate corrosion rate prediction critical for operational safety. This study establishes an average corrosion rate prediction model using the Sparrow Search Algorithm-optimized Light Gradient Boosting Machine (SSA-LightGBM). …”
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A machine learning-based predictive model for predicting early neurological deterioration in lenticulostriate atheromatous disease-related infarction by Zhuangzhuang Jiang, Dongjuan Xu, Hongfei Li, Xiaolan Wu, Yuan Fang, Chen Lou

“…Background and aimThis study aimed to develop a predictive model for early neurological deterioration (END) in branch atheromatous disease (BAD) affecting the lenticulostriate artery (LSA) territory using machine learning. …”
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The Electricity Load Prediction Model for Residential Buildings: A Critical Review of Output Types, Prediction Methods and Driving Factors by Zhenjing Wu, Min Qi, Weiling Zhang, Xudong Zhang, Qiang Yang, Wenyuan Zhao, Bin Yang, Zhihan Lyu, Faming Wang, Zhichao Wang

“…Predictive model building methods were classified as classical, algorithms based on Machine Learning (ML) or Deep Learning (DL) and hybrid methods. …”
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Development and validation of a risk model for prediction of hazardous alcohol consumption in general practice attendees: the predictAL study. by Michael King, Louise Marston, Igor Švab, Heidi-Ingrid Maaroos, Mirjam I Geerlings, Miguel Xavier, Vicente Benjamin, Francisco Torres-Gonzalez, Juan Angel Bellon-Saameno, Danica Rotar, Anu Aluoja, Sandra Saldivia, Bernardo Correa, Irwin Nazareth

“…<h4>Conclusions</h4>The predictAL risk model for development of hazardous consumption in safe drinkers compares favourably with risk algorithms for disorders in other medical settings and can be a useful first step in prevention of alcohol misuse.…”
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From Tension to Triumph: Design and Implementation of an Innovative Algorithmic Metric for Quantifying Individual Performance in Women Volleyball’s Critical Moments by Carlos López-Serrano, María Zakynthinaki, Daniel Mon-López, Juan José Molina Martín

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Assessing Crash Reduction at Stop-Controlled Intersections: A Before-After Study of LED-Backlit Signs Using Crash and Conflict Data by Maziyar Layegh, Ciprian Alecsandru, Matin Giahi Foomani

“…The results showed significant conflict reductions at intersections with LED-backlit signs (BLSs), including 65.5% at night and 46.8% in daylight. …”
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Practical Application of Complementary Regulation Strategy of Run-of-River Small Hydropower and Distributed Photovoltaic Based on Multi-Scale Copula-MPC Algorithm by Xianpin Zhu, Weibo Li, Shuai Cao, Wei Xu

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i-DENV: development of QSAR based regression models for predicting inhibitors targeting non-structural (NS) proteins of dengue virus by Sakshi Gautam, Anamika Thakur, Manoj Kumar

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A novel problem-solving method by multi-computational optimisation of artificial neural network for modelling and prediction of the flow erosion processes by Hossein Moayedi, Atefeh Ahmadi Dehrashid, Binh Nguyen Le

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Stable Parallel Algorithms for Interdisciplinary Computer-Based Online Education with Real Problem Scenarios for STEM Education by Liangfu Jiang, Haoran Yuan

“…In this paper, we analyse and study the interdisciplinary style of stable parallel algorithms for online computer education and real problem scenarios for STEM education. …”
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Comparative Study on Total Organic Carbon Content Logging Prediction Method Based on Machine Learning by TANG Shengshou, YANG Bin, JIN Jiulong, LIU Hongrui, DAI Xingyu, PU Jincheng

“…There are many influencing factors and difficulty in the prediction of total organic carbon content, so it is particularly important to explore the most suitable high-precision prediction method for the prediction of total organic carbon content in this area. …”
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Research on the prediction of blasting fragmentation in open-pit coal mines based on KPCA-BAS-BP by Shuang Liu, Enxiang Qu, Chun LV, Xueyuan Zhang

“…Compared with the unoptimized BP neural network and the BP neural network optimized by the artificial bee colony algorithm (ABC) model, this model has higher prediction accuracy and is more suitable for predicting the blasting block size of open-pit coal mines, it provides a new method for predicting the fragmentation of blasting under the influence of multiple factors, filling the gap in related theoretical research, and has certain practical application value.…”
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microProtein Prediction Program (miP3): A Software for Predicting microProteins and Their Target Transcription Factors by Niek de Klein, Enrico Magnani, Michael Banf, Seung Yon Rhee

“…The algorithm is called miP prediction program (miP3), which is implemented in Python. …”
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A Novel Energy Consumption Prediction Model Integrating Real-Time Traffic State Recognition and Velocity Prediction of BEVs by Yue Li, Yu Jiang, Jianhua Guo, Dong Xie

“…The widespread adoption of battery electric vehicles (BEVs) has highlighted the critical importance of precise energy consumption prediction models to address the problem of range anxiety among drivers. …”
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Multi-Condition Magnetic Core Loss Prediction and Magnetic Component Performance Optimization Based on Improved Deep Forest by Haotian Shi, Zipeng Jin

“…This paper proposes a core loss prediction model based on an improved deep forest algorithm and information entropy-enhanced genetic algorithm. …”
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Accurate Prediction of 327 Rice Variety Growth Period Based on Unmanned Aerial Vehicle Multispectral Remote Sensing by Zixuan Qiu, Hao Liu, Lu Wang, Shuaibo Shao, Can Chen, Zijia Liu, Song Liang, Cai Wang, Bing Cao

“…In this study, multispectral images of rice at various growth stages were captured using an unmanned aerial vehicle, and single-plant rice silhouettes were identified for 327 rice varieties by establishing a deep-learning algorithm. A growth stage prediction method was established for the 327 rice varieties based on the normalized vegetation index combined with cubic polynomial regression equations to simulate their growth changes, and it was first proposed that the growth stages of different rice varieties were inferred by analyzing the normalized difference vegetation index growth rate. …”
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Research on prediction of bottom hole flowing pressure for vertical coalbed methane wells based on improved SSA-BPNN by YU Yang, DONG Yintao, LI Yunbo, BAO Yu, ZHANG Lixia, SUN Hao

Subjects: “…|coalbed methane|sparrow search algorithm|neural network|bottom hole flowing pressure|prediction model…”
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A peak-to-average power ratio reduction algorithm for OTFS systems in satellite-to-ground scenarios by SONG Qiangjian, CHEN Yumeng, ZHU Lidong

Subjects: “…partial transfer sequence algorithm…”
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Spatiotemporally Combined Dimensionality Reduction Algorithm for Optimizing Long-term Operation of Multi-reservoir Systems by CHEN Jia, ZHANG Hanjun, XU Nan

“…To alleviate the “curse of dimensionality” and improve the solution efficiency while ensuring the quality of solutions in optimizing the operation of multi-reservoir systems,this paper proposes a spatiotemporally combined dimensionality reduction algorithm which integrates and improves the dynamic programming with successive approximation (DPSA) and the progressive optimality algorithm (POA).First,a chain-based successive approximation strategy is proposed to expand the DPSA's optimization mode from “single reservoir alternation” to “cascade reservoir chain alternation”,which makes up for the DPSA's shortcomings in dealing with the hydraulic coupling relationships among cascade reservoirs.Then,a dynamic variable decoupling strategy and perturbation mechanism are proposed to deal with the POA's blind search problem and dimensionality problem.Finally,the two improved algorithms are combined,in which the improved POA is applied to solving the optimization problems of cascade reservoir chains under the framework of the improved DPSA.The power generation operation problem of the cascade reservoirs in the Yuan River Basin of Hunan Province and the classical ten-reservoir problem are utilized to test the performance of the proposed algorithm.The proposed algorithm outperforms seven existing alternatives in terms of solution quality and efficiency.The results indicate that the proposed algorithm can effectively alleviate the “curse of dimensionality” in optimizing the operation of multi-reservoir systems,improve the efficiency while ensuring the quality of solutions and has potential to be applied to optimizing the operation of complex large-scale multi-reservoir systems.…”
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A Novel Iterative-SLM Algorithm for PAPR Reduction in 5G Mobile Fronthaul Architecture by Mohammed I. Al-Rayif, Hussein Seleem, Amr Ragheb, Saleh Alshebeili

“…The proposed algorithm uses orthogonal phase vectors construction. …”
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