Modelling and optimisation of solar photovoltaic power using response surface methodology by Abdulrahman Mohammad, Mudhar Al-Obaidi, Hassan Dakkama, Haitham Bahlol

“…The response surface methodology model has indicated a linear relationship between the independent variables and power generated with a coefficient of determination of 98.45%. …”
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Bayesian inference of structured latent spaces from neural population activity with the orthogonal stochastic linear mixing model. by Rui Meng, Kristofer E Bouchard

“…The brain produces diverse functions, from perceiving sounds to producing arm reaches, through the collective activity of populations of many neurons. …”
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Multi-objective optimization of a novel control algorithm and scheduling procedure for optimal use of energy storage systems by Amirhossein Hamzeiyan, Armin Ebrahimi

“…Peak shaving with energy storage systems (ESSs) is a promising approach to optimize energy use, reduce costs, and ensure a more reliable power grid.This paper aims to improve the performance of a novel control algorithm for efficient peak shaving by using sensitivity analysis and multi-objective optimization techniques. …”
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Cognitive Agent-Based Modeling to Optimize Complex Project Management Under Uncertainty by Liliana M. Pantoja-Rojas, Marco A. Alzate-Monroy, Vactor H. Medina-Garcaa, Luis G. Moreno-Sandoval

“…Overall, the study underscores the importance of organizational continuity and the thoughtful design of collaboration parameters to achieve efficient performance in complex project settings. …”
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Review: roles of mycorrhizal symbioses and associated soil microbiomes in ecological restoration by Christine Lethielleux-Juge

“…A similar recovery period was observed for fungal communities in forest restoration, where ectomycorrhizal mycorrhizal fungi (EMF) species dominate, and diversity increased with time post-revegetation, influenced by edaphic variables and tree species. Under heavy metal (HM) contamination, microorganism classes, enzymes, and AMF efficiency vary with time, soil parameters, restoration treatments, plant species, and levels of soil contamination, with Proteobacteria and Actinobacteria being often predominant. …”
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Unsupervised selective labeling for semi-supervised industrial defect detection by Jian Ge, Qin Qin, Shaojing Song, Jinhua Jiang, Zhiwei Shen

“…This has motivated a shift towards semi-supervised learning (SSL), which leverages labeled and unlabeled data to improve learning efficiency and reduce annotation costs. This work proposes the unsupervised spectral clustering labeling (USCL) method to optimize SSL for industrial challenges like defect variability, rarity, and complex distributions. …”
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Prox-STA-LSTM: A Sparse Representation for the Attention-Based LSTM Networks for Industrial Soft Sensor Development by Yurun Wang, Yi Huang, Dongsheng Chen, Longyan Wang, Lingjian Ye, Feifan Shen

“…For deep learning based soft sensors, the spatiotemporal attention (STA)-LSTM is a newly emerged technique which provides efficient predictions for quality variables of industrial processes. …”
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Active RIS-NOMA Uplink in URLLC, Jamming Mitigation via Surrogate and Deep Learning by Ghazal Asemian, Mohammadreza Amini, Burak Kantarci

“…The complexity of the optimization problem, involving numerous interacting variables, leads us to develop a deep regression model to predict optimal network configurations, providing a computationally efficient approach as well as reducing the signaling overhead. …”
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Calculation and Forecast of Glacial Feeding in River Basins by V. G. Konovalov

“…Index δ for the upper reaches of the Rhone River turned out to be not only a representative characteristic of changes in the vegetation period and annual runoff of the river, but also an efficient argument for the super-long-range prediction of these variables for 2025–2054 years.…”
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PRODUCTION AND INCOME ANALYSIS OF DRIED FISH BUSINESS IN BENGKULU CITY by Bambang Sumantri, Irnad, Winta Septria, Melly Suryanti, Widya Kartika Laksmawati

“…R/C Ratio analysis obtained efficiency values of 2.13 and 1.91 respectively so the business is carried out proved to be efficient. …”
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Randomization-Driven Hybrid Deep Learning for Diabetic Retinopathy Detection by A. M. Mutawa, G. R. Hemalakshmi, N. B. Prakash, M. Murugappan

“…Timely identification is crucial for efficient intervention, as untreated diabetic retinopathy can progress to irreversible vision loss. …”
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Modal Analysis of QP and LP Solution in Steady-state Optimization Layer of Two-layer Structure MPC by WANG Hongrui, ZHANG Xin, LIU Bowen, LIN Na, ZOU Tao

“…Simulation results prove that QP had better continuity than LP when the weight coefficient of decision variables are changed, and the weight coefficient of QP can more accurately adjust the bias of decision variables. …”
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Cost-effective process design for methanol synthesis from carbon dioxide hydrogenation by Sheng-Zhong Huang, Chih-Yao Lin, Chianghui Wang, Akhmat Fauzan Saputra, Henggar Yudha Hananto, Nicolas Justin Sutanto, Anggit Raksajati, Vincentius Surya Kurnia Adi

“…Accordingly, this research introduces an optimization framework capable of handling diverse process configurations, operating variables, and their interactions. This approach enables effective optimization using total annual cost (TAC) as the objective function and significantly enhances process design efficiency. …”
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Multi-Objective Optimal Design of 200 kW Permanent Magnet Synchronous Motor Based on NSGA-II by Chengxu Sun, Qi Li, Tao Fan, Xuhui Wen, Ye Li, Hongyang Li

“…Interior permanent magnet synchronous motors (IPMSMs) are widely applied as drive motors in electric vehicles because they have the advantages of high power density, high efficiency, and excellent dynamic performance. This paper introduces a framework for multi-objective optimization, tailored for the demands of V-Shaped IPMSMs, which involves high-dimensional variables. …”
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COVID-19 recovery: benefits of multidisciplinary respiratory rehabilitation by Wim Janssens, Greet Hermans, Rik Gosselink, Daniel Langer, Thierry Troosters, Hilde Beyens, Stephanie Everaerts, Arne Heyns, Natalie Lorent

“…Impressive results on physical recovery were determined after 6 weeks and 3 months, with significant improvement of lung function, muscle force and exercise capacity variables. …”
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Codesign of Transmit Waveform and Receive Filter with Similarity Constraints for FDA-MIMO Radar by Qiping Zhang, Jinfeng Hu, Xin Tai, Yongfeng Zuo, Huiyong Li, Kai Zhong, Chaohai Li

“…Finally, the Riemannian limited-memory Broyden–Fletcher–Goldfarb–Shanno (RL-BFGS) algorithm is employed to optimize the variables in parallel. Simulation results demonstrate that our method achieves a 0.6 dB improvement in SINR compared to existing methods while maintaining competitive computational efficiency. …”
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Investigating factors affecting the quality of water resources by multivariate analysis and soft computing approaches by Bing Cheng, Xinyu Liu, Keke Guo, Ahmad Rastegarnia

“…Therefore, Na+, Cl+, Na%, CO3 −, and SO4 2− were used as input variables (independent variables), and EC, TDS, and SAR were used as output variables (dependent variables). …”
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Robust Optimization Research of Cyber–Physical Power System Considering Wind Power Uncertainty and Coupled Relationship by Jiuling Dong, Zilong Song, Yuanshuo Zheng, Jingtang Luo, Min Zhang, Xiaolong Yang, Hongbing Ma

“…Furthermore, the deterministic power balance constraints are relaxed into inequality constraints that account for wind power forecasting errors through fuzzy variables. The lower-level model focuses on minimizing traffic load shedding by establishing a topology–function-constrained information network traffic model based on the maximum flow principle in graph theory, thereby improving the efficiency of network flow transmission. …”
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Research on Robust Adaptive Model Predictive Control Based on Vehicle State Uncertainty by Yinping Li, Li Liu

“…To overcome these limitations, three key innovations are introduced: a three-degree-of-freedom vehicle dynamic model integrated with recursive least squares-based online estimation of tire slip stiffness for real-time lateral force compensation; an adaptive weight adjustment mechanism that dynamically balances control energy consumption and tracking accuracy by tuning cost function weights based on real-time state errors; and a dynamic constraint relaxation strategy using slack variables with variable penalty terms to resolve infeasibility while suppressing excessive constraint violations. …”
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Retrieval of carbon and inorganic phosphorus during hydrothermal carbonization: ANN and RSM modeling by Abolfazl Shokri, Mohammad Amin Larki, Ahad Ghaemi

“…Next, Multilayer Perceptron (MLP) and Radial Basis Function (RBF) were used to compare the results and improve the model fit. …”
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