Optimization of stope dimensions using response surface method coupling a hybrid chaos-genetic algorithm by Ming lan, Hanwen Jia, Ju Ma

“…The interaction between variables within this framework was carefully considered when defining the objective functions for optimization. …”
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A robust deep learning approach for photovoltaic power forecasting based on feature selection and variational mode decomposition by Mokhtar Ali, Abdelkerim Souahlia, Abdelhalim Rabehi, Mawloud Guermoui, Ali Teta, Imad Eddine Tibermacine, Abdelaziz Rabehi, Mohamed Benghanem

“…Three feature selection methods---ReliefF, Minimum Correlation, and Minimum Redundancy Maximum Relevance (MRMR)---are employed to identify the most relevant input variables from a dataset collected in the Ghardaia region. …”
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Optimizing the Spectrum and Power Allocation for D2D-Enabled Communication Systems Using DC Programming by Guomei Gan, Yanhu Huang, Qiang Wang

“…Indeed, the devices can communicate with each other in a D2D system, and the base station (BS) can share the spectrum with D2D users, which can efficiently improve the spectrum and energy efficiency. …”
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Optimized Blade Design of Counter-Rotating-Type Pump-Turbine Unit Operating in Pump and Turbine Modes by Jin-Woo Kim, Jun-Won Suh, Young-Seok Choi, Kyoung-Yong Lee, Toshiaki Kanemoto, Jin-Hyuk Kim

“…The pump and turbine mode efficiencies of the unit were selected as the objective functions and they combined into a single specific objective function with the weighting factors. …”
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Socio‑Economic Determinants of Construction Sector Development by Florian Gerth, Martin O’Brien, Karol S. Sikora

“…The empirical analysis applied uses data from the Statistical Yearbook of Cambodia (2021) to analyze the statistical relationship between socioeconomic , economic, demographic variables and construction. To do this, the study conducts a combination of regression analyses, Ordinary Least Squares in conjunction with Methods-of-Moments, while applying rigor to guarantee compliance with the CLR function assumptions. …”
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Risk-averse Robust Interval Economic Dispatch for Power Systems with Large-scale Wind Power Integration by Zhenjia Lin, Haoyong Chen, Jinbin Chen, Jianping Huang, Mengshi Li

“…Differing from existing interval optimization (IO) approaches that merely rely on the upper and lower boundaries of random variables, the distribution information retained in the historical data is introduced to the IO method in this paper. …”
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Drug Release Analysis and Optimization for Drug-Eluting Stents by Hongxia Li, Yihao Zhang, Bao Zhu, Jinying Wu, Xicheng Wang

“…The diffusion coefficients and the coating thickness are selected as design variables. An adaptive optimization approach based on kriging surrogate model is proposed to optimize the lifetime of the drug in artery wall. …”
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An Optimization Strategy for Generator Start-up Sequence After Blackouts Considering the Cyber System Fault by Mingming LI, Lei SUN, Yinghao MA

“…An optimal start-up sequence model of generators is proposed with the expectation of maximum power systems’ total generation as objective function, and taking into account the constraints including the start-up time constraint of generator units, the auxiliary variables constraint related to the cyber system fault, and the start-up power constraint of generator units. …”
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An Adiabatic-Expansion-Induced Perturbation Study on Gas–Aerosol Partitioning in Ambient Air—Formation of NH₄NO₃ and Microdroplet Nitrogen Fixation (2) by Yating Gao, Qinchu Fan, Yujiao Zhu, Hengqing Shen, Qi Yuan, Yang Gao, Huiwang Gao, Xiaohong Yao

“…Our results indicate the adiabatic-expansion-induced generation of NH₃ + HNO₃ at ultrafast formation rates, with campaign-dependent stable stoichiometric ratios of HNO₃ to NH₃, as well as highly variable occurrence frequencies and efficiencies. These findings suggest that microdroplet redox reactions are more likely responsible for the generation of NH₃ + HNO₃ than conventional atmospheric NH₃ chemistry. …”
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Double and integer multi-objective optimization of solar HDH desalination system with bubble column dehumidifier: An artificial neural network approach by Alireza Naeini, Alireza Jalali, Ehsan Houshfar

“…A neural network model is utilized to predict how the objective functions vary with six decision variables. The chosen optimization approach utilizes the genetic algorithm (GA) method. …”
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Adaptive neighbourhood for locally and globally tuned biogeography based optimization algorithm by Parimal Kumar Giri, Sagar S. De, Satchidananda Dehuri

“…BBO has demonstrated good performance on various unconstrained and constrained benchmark functions. It has also been applied to real world optimization problems of type linear or nonlinear, nominal or ordinal as well as mixed variables. …”
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Rational and Irrational Investor Sentiments and Stock Market Returns: Evidence from the Tehran Stock Exchange by Mohammad Nadiri, Hamid Reza Panahian

“…In the first step, we used an autoregressive distributed lag (ARDL) technique to regress macroeconomic fundamental variables on individual and institutional investor sentiments to decompose the sentiment variables into rational and irrational components. …”
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Application of a novel metaheuristic algorithm inspired by connected banking system in truss size and layout optimum design problems and optimization problems by Mehrdad Nemati, Yousef Zandi, Jamshid Sabouri

“…Abstract Optimum design of truss structures can be a challenging and difficult field of study specially if an optimum design problem is comprised of continuous and discrete decision variables such as in truss size and layout optimization problems. …”
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Comparative evaluation of machine learning models for enhancing diagnostic accuracy of otitis media with effusion in children with adenoid hypertrophy by Xiaote Zhang, Qiaoyi Xie, Ganggang Wu

“…Current non-invasive screening modalities rely predominantly on acoustic immittance measurements, which demonstrate variable diagnostic performance. Given the urgent need for improved diagnostic methods and extensive characterization of risk factors for OME in AH children, developing diagnostic models represents an efficient strategy to enhance clinical identification accuracy in practice.ObjectiveThis study aims to develop and validate an optimal machine learning (ML)-based prediction model for OME in AH children by comparing multiple algorithmic approaches, integrating clinical indicators with acoustic measurements into a widely applicable diagnostic tool.MethodsA retrospective analysis was conducted on 847 pediatric patients with AH. …”
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CGF with Bio-Oss collagen as grafting materials for simultaneous implant placement after osteotome sinus floor elevation: a prospective study by Bashar Shahood, Seba Harphoush, Belal O. M. Muhaisen, Jing Qiu

“…The Implants Survival Rate (ISR) was the primary outcome variable. Secondary outcome variables included radiographic measurements assessed at four follow-up time points, the Implant Stability Quotient (ISQ), and bone density (B). …”
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Engineering students' perceptions and actual use of AI-based math tools for solving mathematical problems by Kimberly F. Garcia, Ardvin Kester S. Ong, Ma. Janice J. Gumasing, Cesar Romeo V. Delos Reyes

“…The objective of this study was to evaluate the variables that influenced the engineering students' perceptions of adoption and actual academic use of AI-based math tools as academic assistance. …”
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FORMAL REPRESENTATION OF THE PIXEL-BY-PIXEL CLASSIFICATION PROCESS USING A MODIFIED WANG-MENDEL NEURAL NETWORK by Oleksii Kolomiitsev, Volodymyr Pustovarov

“…The following results were obtained: the use of a fuzzy Wang-Mendel neural network as a classifier of a modified U-Net decoder based on the representation of membership functions in IFST2 and the implementation of phasing, aggregation and activation operations using operations on IFST2; introduction of an additional operation of type reduction in the phase of dephasification of the original variable based on the classical method of the center of gravity (centroid); introduction of several outputs of the network to recognize the appropriate number of classes (subclasses) of the subject area. …”
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A Novel Exploration Stage Approach to Improve Crayfish Optimization Algorithm: Solution to Real-World Engineering Design Problems by Harun Gezici

“…It is deprived of a stochastic variable and is not able to generate an applicable balance between exploration and exploitation. …”
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Research on the Stability Prediction and Optimization of CNC Milling Based on Bagging–NSGAⅡ Under the Influence of Multiple Factors by Congying DENG, Qian YOU, Yang ZHAO, Lijun LIN, Guofu YIN

“…Taking these process parameters (<italic>x</italic>, <italic>y</italic>, <italic>z</italic>, <italic>d</italic>, <italic>h</italic>, <italic>n</italic>, <italic>a</italic>_p, <italic>a</italic>_e, <italic>f</italic>_z) as design variables, a multi-objective optimization model is constructed to balance machining efficiency and tool life. …”
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Integrated neural network framework for multi-object detection and recognition using UAV imagery by Mohammed Alshehri, Tingting Xue, Tingting Xue, Ghulam Mujtaba, Yahya AlQahtani, Nouf Abdullah Almujally, Ahmad Jalal, Ahmad Jalal, Hui Liu, Hui Liu, Hui Liu

“…In the end, using an attention function, Vision Transformer-based models classify vehicles seen from above. …”
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