Multi-period optimisation of flexible natural gas production network infrastructure with an operational perspective: A mixed integer linear programming approach by Noor Yusuf, Roberto Baldacci, Ahmed AlNouss, Tareq Al-Ansari

“…Notably, the case considering fixed and operating cost variables together as a single cost variable in the objective function, referred to as annualised cost (case C), offered optimal cost quantification with relaxed technical constraints. …”
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Optimization of Adaptive I²H ∞ Control Method Based on Multiple Input Sensors by Yu Gu, Hanyang Li, Zeting Mei, Hao Wen, Yuanxiong Jin, Wenxuan Dong

“…The core contributions of this study include: 1) Designing a multi-sensor current reference estimator to dynamically generate the optimal electromagnetic torque through state variables such as wheel speed, acceleration, slope, and human factor database (heart rate, subjective score, fatigue index) to achieve real-time prediction of rider demand; 2) Proposing an adaptive current reference value estimation algorithm that integrates feedforward compensation and error feedback to ensure smooth switching of assistance modes and suppress sensor noise; 3) Developing an intention-induced H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> robust current tracking controller that significantly enhances the system&#x2019;s robustness to parameter fluctuations and external disturbances by optimizing the H<inline-formula> <tex-math notation="LaTeX">$\infty $ </tex-math></inline-formula> norm of the closed-loop transfer function, while supporting personalized riding assistance.…”
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Proposing Optimized Random Forest Models for Predicting Compressive Strength of Geopolymer Composites by Feng Bin, Shahab Hosseini, Jie Chen, Pijush Samui, Hadi Fattahi, Danial Jahed Armaghani

“…We present a comparative analysis of two hybrid models, Harris Hawks Optimization with Random Forest (HHO-RF) and Sine Cosine Algorithm with Random Forest (SCA-RF), against traditional regression methods and classical models like the Extreme Learning Machine (ELM), General Regression Neural Network (GRNN), and Radial Basis Function (RBF). Using a comprehensive dataset derived from various scientific publications, we focus on key input variables including the fine aggregate, GGBS, fly ash, sodium hydroxide (NaOH) molarity, and others. …”
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Triangular Fuzzy Finite Element Solution for Drought Flow of Horizontal Unconfined Aquifers by Christos Tzimopoulos, Nikiforos Samarinas, Kyriakos Papadopoulos, Christos Evangelides

“…The initial water table is assumed to be curvilinear, following the form of an inverse incomplete beta function. To account for uncertainties in the system, the hydraulic parameters—hydraulic conductivity (K) and porosity (S)—are treated as fuzzy variables, considering sources of imprecision such as measurement errors and human-induced uncertainties. …”
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The impact of digital economy on urban-rural income gap under government intervention by LE Yang, GAO Dongxi, ZHANG Yi, GUO Wei, CHEN Yi

“…The research results show that in the current or future period, we should vigorously improve the digital economy level in rural areas by the visible hand of government, and take practical measures to realize the combination of promising government and efficient market, so that the digital economy can give full play to its inclusiveness of converging urban-rural income gap, and further promote common prosperity.…”
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Cognitive performance classification of older patients using machine learning and electronic medical records by Monika Richter-Laskowska, Ewelina Sobotnicka, Adam Bednorz

“…Various ML techniques are evaluated to classify cognitive performance levels based on input features such as sociodemographic variables, lab results, comorbidities, Body Mass Index (BMI), and functional scales. …”
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Thermoelastic damping in piezothermoelastic nanobeam resonators under the strain gradient theory with micro-inertia and non-fourier heat conduction by Olha Hrytsyna, Maryan Hrytsyna

“…To account for small-scale effects, the Helmholtz free energy density is defined as a function of the strain tensor, strain gradient tensor, electric field vector, and temperature field, considering these parameters as independent state variables. …”
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Diversity and interdomain networks of bacterial, pico-protist and nano-protist communities in a marine ranching by Xinyi Zheng, Xin Guo, Xin Guo, Xiaoqing Lin, Cheng Huang, Lingfeng Huang

“…Interdomain microbial networks showed the highest robustness and information transfer efficiency in autumn. This pattern was linked not only to environmental conditions but also to how specialized the protist communities became during that time. …”
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Optimal Design Method of Integrated Energy Systems Considering Staged Planning and Equipment Replacement by Lei ZOU, Yiming TANG, Zhuping LIU, Zhengyong WU, Chao FANG, Chaoqun WANG, Fushuan WEN

“…Then, with the whole project cycle as the optimization time scale, the relationship between the equipment installation year and the current remaining life is modeled by introducing the equipment selection and operation decision variables. Finally, considering the influence of economic factors such as nominal interest rates and inflation rates, an objective function, involving investment costs, operating costs, and equipment residual value income, is constructed, with the optimal economical performance as the goal. …”
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Interval Economic Dispatch for Commercial Campus Integrated Energy System with Demand Response Considering Multiple Uncertainties by Xuan Sheng, Shunjiang Lin, Weikun Liang, Yue Pan, Mingbo Liu

“…Test results from actual CCIES demonstrate that the DR can improve the economy and reduce the uncertain fluctuation range of both the objective function and state variables. The ED result can maintain an economical and secure operation under multiple uncertain fluctuations.…”
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Anomalous Behavior in Weather Forecast Uncertainty: Implications for Ship Weather Routing by Marijana Marjanović, Jasna Prpić-Oršić, Anton Turk, Marko Valčić

“…This allows uncertainty to be quantified not as a static estimate, but as a function sensitive to both variable type and prediction horizon. …”
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Construction Concrete Price Prediction Based on a Double-Branch Physics-Informed Neural Network by Kaier Shi, Ruiqing Han, Zhipeng Li, Pan Guo

“…Moreover, a comparative analysis using a traditional ANN model is conducted to verify the efficiency of the DB-PINN model, and a parameter sensitivity analysis is performed to reveal the impact of each raw material price factor and macroeconomic indicator on the construction concrete price. …”
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Peak Arm Current Reduction of Modular Multilevel Converter Based on Particle Swarm Optimizer for Circulating Current Injections by Riyadh Toman Thahab, Tahani Hamodi Al-Mhana

“…The magnitude and phase of the injected components are treated as variables in the optimisation process, with the goal of minimising the peak arm current as the cost function. …”
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Commercial Vehicle Ride Comfort Optimization Based on Intelligent Algorithms and Nonlinear Damping by Shuilong He, Keren Chen, Enyong Xu, Wei Wang, Zhansi Jiang

“…The sum of the frequency-weighted RMS of the driver seat acceleration, the RMS of dynamic tyre load, and suspension working space is taken as the objective function in this article, using nonlinear damping coefficients and stiffness of suspension as design variables. …”
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Optimization Study of PVT Coupled Water Loop Heat Pump Energy Supply System by Lv Tiangang, Liu Bing, Wu Jun, Zhu Li, Hou Jingxuan

“…By employing the Hooke-Jeeves algorithm, the system's design and operation parameters were optimized with annual cost and system COP as objective functions. Design variables included PVT inclination, azimuth, area, heat pump capacity, and tank volume, while operational variables were PVT backplate temperature and tank temperature. …”
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Optimization of K-Shaped Metal Sealing Ring for Subsea Tubing Hanger Based on Response Surface Method by Huan Xie, Hongxia Zhang, Yiwei Fan, Liyuan Liu, Wei Zeng

“…To address the issue of low optimization efficiency due to the need for repeated finite element calculations during the optimization process, quadratic response surface models are established for the sealing performance indicators of the K-shaped seal ring, which were then used as the optimization objective functions to enhance the optimization efficiency. …”
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On the development of a practical Bayesian optimization algorithm for expensive experiments and simulations with changing environmental conditions by Mike Diessner, Kevin J. Wilson, Richard D. Whalley

“…The method is validated on two synthetic test functions, and the effects of the noise level, the number of environmental parameters, the parameter fluctuation, the variability of the uncontrollable parameters, and the effective domain size are investigated. …”
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Identification of Factors Affecting Project Financing Risk by Gholamreza Sharafi, Kiamars Fathi Hafashjani, Faegh Ahmadi

“…Risk management is now an important part of project management and has a specific function for improving the efficiency of implementing the project, saving prices, and improving the profitability of projects. …”
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Fuzzy Goal Programming Procedure to Bilevel Multiobjective Linear Fractional Programming Problems by Mahmoud A. Abo-Sinna, Ibrahim A. Baky

“…The method of variable change on the under- and over-deviational variables of the membership goals associated with the fuzzy goals of the model is introduced to solve the problem efficiently by using linear goal programming (LGP) methodology. …”
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Machine learning-based model for acute asthma exacerbation detection using routine blood parameters by Youpeng Chen, Junquan Sun, Yabang Chen, Enzhong Li, Jiancai Lu, Huanhua Tang, Yifei Xie, Jiana Zhang, Lesi Peng, Haojie Wu, Zhangkai J. Cheng, Baoqing Sun

“…Background: Acute asthma exacerbations (AAEs) are a leading cause of asthma-related morbidity and mortality, especially in resource-limited settings where pulmonary function tests are unavailable or when patients are unable to cooperate with testing. …”
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