Forward Predicting Chromatic-Optical Parameters of the Mixed Light of White-Red Light-Emitting Diode Configurations Based on Deep Learning Algorithms by Songsheng Lin, Huanting Chen, Yin Zheng, Quanji Xie, Xuehua Shen, Huichuan Lin, Shuo Lin, Yan Li

“…Four deep learning algorithms were evaluated. Each model was trained to reconstruct the SPD curves and predict the corresponding optical and chromatic parameters. …”
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Optimizing Pile Bearing Capacity Prediction Using Specific Random Forest Models Optimized by Meta-Heuristic Algorithms for Enhanced Geomechanically Applications by Nengyuan Chen

“…To achieve highly accurate predictions of Pile Bearing Capacity (PBC), the study employs a cutting-edge approach featuring Specific Random Forest (RF) prediction models, strategically enhanced with two potent meta-heuristic algorithms: the Snake Optimizer (SO) and the Equilibrium Optimizer (EO). …”
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Predicting low birth weight risks in pregnant women in Brazil using machine learning algorithms: data from the Araraquara cohort study by Audêncio Victor, Francielly Almeida, Sancho Pedro Xavier, Patrícia H.C. Rondó

“…Abstract Background Low birth weight (LBW) is a critical factor linked to neonatal morbidity and mortality. Early prediction is essential for timely interventions. This study aimed to develop and evaluate predictive models for LBW using machine learning algorithms, including Random Forest, XGBoost, Catboost, and LightGBM. …”
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Large-scale terminal access algorithm based on slot ALOHA and adaptive access class barring by Zhenyu ZHU, Xiaorong ZHU, Yan CAI, Hongbo ZHU

“…In order to solve the problem of high collision rate and low timeliness of large-scale terminals access in the Internet of things, a large-scale terminal access algorithm based on slot ALOHA and adaptive access class barring (ACB) was proposed.Firstly, the services were classified based on the data from each terminal by the volume of the services processed and the requirements for delay.For the services that were not time-sensitive and whose effective data portion was less than 1 000 bit, a slot-based ALOHA-based competitive access method was used.ACB-based random access was used for the services that were time-sensitive or whose data portion was greater than 1 000 bit.On this basis, a method was proposed for predicting the access application volume based on the quantitative estimation, and dynamically adjusting the ACB control parameters based on this predicted value.Simulation results show that compared with other existing access algorithms, the proposed algorithm reduces the collision rate and improves the system access success rate under the premise of ensuring the high priority service delay requirements.…”
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Advanced Control Algorithm for Shunt Active Power Filter: Enhancing Power Quality in Autonomous Grids by Agata Bielecka

“…This paper proposes an advanced predictive control algorithm with feedback from the supply current developed for a shunt active power filter. …”
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Implementing a transmural model of early palliative care in advanced dementia: the use of a hybrid effectiveness-implementation study design by Allyn Hum, Palvinder Kaur, Wen Yang Goh, Riyin Tay, Han Yee Neo, Mervyn Yong Hwang Koh, Noorhazlina Binte Ali, Wee Shiong Lim, Yu-Ling Jackie Tan, Huei Yaw Wu, Palvannan Kannapiran, Hwee Teng Robyn Tan, Yan Sun, Chin Ee Ong, Ravinder Singh Sachdev, Zhi Jun Low, Lee Hung Tey, Woan Shin Tan, Yew Yoong Ding

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A Predictive Model of the Photosynthetic Rate of Chili Peppers Using Support Vector Regression and Environmental Multi-Factor Analysis by Bin Li, Bo Qiao, Qianyu Zhao, Dan Yang, Rongcheng Zhu, Zhexuan Wang, Yujie Yang

Subjects: “…photosynthetic rate prediction model…”
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Modeling and Discovering Direct Causes for Predictive Models by Yizuo Chen, Amit Bhatia

“… We introduce a causal modeling framework that captures the input-output behavior of predictive models (e.g., machine learning models). The framework enables us to identify features that directly cause the predictions, which has broad implications for data collection and model evaluation. …”
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Energy Optimization in Ultrasound Tomography Through Sensor Reduction Supported by Machine Learning Algorithms by Bartłomiej Baran, Tomasz Rymarczyk, Dariusz Majerek, Piotr Szyszka, Dariusz Wójcik, Tomasz Cieplak, Marcin Gąsior, Marcin Marczuk, Edmund Wąsik, Konrad Gauda

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Research on optimal selection of runoff prediction models based on coupled machine learning methods by Xing Wei, Mengen Chen, Yulin Zhou, Jianhua Zou, Libo Ran, Ruibo Shi

Subjects: “…Runoff prediction…”
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Hyperband-Optimized CNN-BiLSTM with Attention Mechanism for Corporate Financial Distress Prediction by Yingying Song, Monchaya Chiangpradit, Piyapatr Busababodhin

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A Machine Learning Approach to Predict Site Selection from the Perspective of Vitality Improvement by Bin Zhao, Hao Zheng, Xuesong Cheng

“…To enhance site selection and planning efficiency, we developed a predictive model integrating Artificial Neural Networks (ANNs) and Genetic Algorithms (GAs). …”
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Suggesting a Novel Hybrid Approach for Predicting Solar Irradiance in the Qinghai Province of China by Baran Yılmaz, Rachel Samra

“…This work aims to provide a hybrid model using machine learning to accurately predict solar Direct normal irradiance with the least amount of error. …”
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Model Predictive Control of Electric Water Heaters in Individual Dwellings Equipped with Grid-Connected Photovoltaic Systems by Oumaima Laguili, Julien Eynard, Marion Podesta, Stéphane Grieu

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Bond behavior of galvanized iron fiber reinforced concrete with recycled coarse aggregate and model prediction using machine learning by Md. Jahidul Islam, Ummul Wara Labiba, Tasfiah Faisal Chowdhury, Md. Shahjalal, Tanvir Mustafy, Tanvir Hassan Tusher

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A novel hybrid machine learning approach for δ13C spatial prediction in polish hard-water lakes by Himan Shahabi, Ataollah Shirzadi, Alicja Ustrzycka, Natalia Piotrowska, Janusz Filipiak, Marzieh Hajizadeh Tahan

Subjects: “…Carbon-13 predicting…”
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Advanced KNN-based cost-efficient algorithm for precision localization and energy optimization in dynamic underwater sensor networks by Nadia Shamshad, Lei Wang, Kiran Saleem, Danish Sarwr, Salil Bharany, Ahmad Almogren, Jaeyoung Choi, Ateeq Ur Rehman, Ayman Altameem

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A Probability Integral Parameter Inversion Method Integrating a Selection-Weighted Iterative Robust Genetic Algorithm by Chuang Jiang, Wei Liu, Lei Wang, Xu Zhu, Hao Tan

“…However, the use of traditional genetic algorithms (GA) for inversion prediction has problems such as poor resistance to differences, and the accuracy of inversion parameters is affected when key monitoring points are missing. …”
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Predictive framework of vegetation resistance in channel flow by Fengcong Jia, Weijie Wang, Yu Han, Jiayu Du, Yue Zhang, Zihan Liu, Hairong Gao

“…To improve predictive performance, optimization algorithms such as PSO, WSO, and RIME were applied. …”
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Real-time prediction of port water levels based on EMD-PSO-RBFNN by Lijun Wang, Shenghao Liao, Sisi Wang, Jianchuan Yin, Ronghui Li, Jingyu Guan

Subjects: “…port water level prediction…”
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