Modeling Spatial Data with Heteroscedasticity Using PLVCSAR Model: A Bayesian Quantile Regression Approach by Rongshang Chen, Zhiyong Chen

“…We apply a Bayesian quantile regression (BQR) of the partially linear varying coefficient spatial autoregressive (PLVCSAR) model for spatial data to improve the prediction of performance. …”
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Life cycle assessment and multicriteria decision making analysis of additive manufacturing processes towards optimal performance and sustainability by Jayant M. Raut, Prashant B. Pande, Kamlesh V. Madurwar, Rajesh M. Bhagat, Satyajit S. Uparkar, Nilesh Shelke, Haytham F. Isleem, Arpita, Vikrant S. Vairagade

“…This methodology makes estimates of not only the mean impact but also allows quantification of the uncertainties through confidence intervals and dynamic LCA. Stochastic Forest algorithm will enhance the traditional MCDA by weighting decision criteria like cost, environmental impact, and durability, in a more dynamic manner aligning to real-time manufacturing performance for better decision-making. …”
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Water quality index modelling and its application on artificial intelligence (AI) in conjunction with machine learning (ML) methodologies for mapping surface water potential zones... by Abhijeet Das

“…To evaluate the contamination level, a basic standard reference i.e., World Health Organization guidelines is implanted to decipher the values ranging from natural to anthropogenic contribution.In the Mahanadi River Basin, Odisha, however, this study has highlighted the evaluation of surface water quality (WQ) for drinking reasons by the combined use of Machine Learning (ML) methodologies like Genetic Algorithm Particle Swarm Optimization-based WQI (GAPSO-WQI), with dependability-oriented decision-making approaches such as Firefly Algorithm (FA) and Algorithm of Weeds (AW), that have been used for river water quality monitoring and assessment due to their dependability and feasibility. …”
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Evaluating Maize Residue Cover Using Machine Learning and Remote Sensing in the Meadow Soil Region of Northeast China by Zhengwei Liang, Jia Du, Weilin Yu, Kaizeng Zhuo, Kewen Shao, Weijian Zhang, Cangming Zhang, Jie Qin, Yu Han, Bingrun Sui, Kaishan Song

“…The Google Earth Engine (GEE) and remote sensing images from 2019 to 2023 were used to obtain spectral characteristics before the maize seedling stage in Northeast China, followed by constructing the CRC estimation models using machine learning algorithms. To avoid the impact of multicollinearity among data, three machine learning algorithms—ridge regression (RR), partial least squares regression (PLSR), and least absolute shrinkage and selection operator (LASSO)—were employed. …”
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Towards a complete classification of holographic entropy inequalities by Ning Bao, Keiichiro Furuya, Joydeep Naskar

“…Thus, by virtue of the argued completeness of the contraction map proof method, the problem of finding all holographic entropy inequalities is equivalent to the problem of finding all contraction maps, which we translate to a problem of finding all image graph partial cubes. We give an algorithmic solution to this problem and characterize the complexity of our method. …”
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Adaptive Control and Market Integration: Optimizing Distributed Power Resources for a Sustainable Grid by Josue N. Otshwe, Bin Li, Songsong Chen, Feixiang Gong, Bing Qi, Ngouokoua J. Chabrol

“…System performance is improved using advanced control strategies together with real-time market-responsive changes and predictive algorithms. The efficacy of the proposed methodology is validated through a detailed simulation of a small island grid using mixed-integer linear programming (MILP) and particle swarm optimization (PSO), which demonstrates significant operational improvements. …”
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Hybrid optimized data aggregation for fog computing devices in internet of things by M. Jalasri, S. Manikandan, Arthur Davis Nicholas, S. Gobimohan, Naarisetti Srinivasa Rao

“…In this work, a new and novel hybrid optimization technique based on TABU Search (TS), Particle Swarm Optimization (PSO), and River Formation Dynamics (RFD) algorithms were proposed. …”
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Hermetically sealed ecodesign distribution transformer weight optimization considering power losses and total ownership cost (TOC) by Mohammad Hassan Hashemi, Ulas Kilic

“…Specifically, the study employs Differential Evolution (DE), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO) algorithms to compare their efficacy against conventional design approaches. …”
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ICARUS at the Short-Baseline Neutrino Program: First Results by Maria Artero Pons

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Hierarchical Multi-UAV Path Planning for Urban Low Altitude Environments by Haoxiang Lei, Yuehao Yan, Jilong Liu, Qiang Han, Zhouguan Li

“…In order to improve these problems, we combine the Ant Colony Algorithm (ACO) with the Particle Swarm Algorithm (PSO), and utilize the early and fast convergence of the PSO to generate a suboptimal solution as the initial condition of the pheromone distribution of the ACO. …”
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Forecasting loan, deferred rate and customer segmentation in banking industry: A computational intelligence approach by Mahtab Vasheghani, Ebrahim Nazari Farokhi, Behrooz Dolatshah

“…This study proposes a novel hybrid model integrating Multi-Layer Perceptron (MLP) neural networks with Self-Adaptive Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) frameworks. …”
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Prediction of pulmonary embolism by an explainable machine learning approach in the real world by Qiao Zhou, Ruichen Huang, Xingyu Xiong, Zongan Liang, Wei Zhang

“…To address this, we employed an artificial intelligence–based machine learning algorithm (MLA) to construct a robust predictive model for PE. …”
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Design of Ricker Wavelet Neural Networks for Heat and Mass Transport in Magnetohydrodynamic Williamson Nanofluid Boundary-Layer Porous Medium Flow with Multiple Slips by Zeeshan Ikram Butt, Muhammad Asif Zahoor Raja, Iftikhar Ahmad, Muhammad Shoaib, Rajesh Kumar, Syed Ibrar Hussain

“…The solver employs a hybrid approach that combines genetic algorithms, serving as a global search method, with sequential quadratic programming, which functions as a local optimization technique. …”
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Achieving high precision and productivity in laser machining of Ti6Al4V alloy: A comprehensive study using a n-predictor polynomial regression model and PSO algorithm by Avinash Chetry, Sandesh Sanjeev Phalke, Arup Nandy

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An Optimization Method for Multi-Functional Radar Network Deployment in Complex Regions by Yi Han, Xueting Li, Xiangliang Xu, Zhenxing Zhang, Tianxian Zhang, Xiaobo Yang

“…Experimental results demonstrate the superiority of the MOPSO-DT algorithm over two existing algorithms across a variety of deployment cases, highlighting its enhanced efficiency, effectiveness, and stability. …”
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Optimization of Ship Permanent Magnet Synchronous Motor ADRC Based on Improved QPSO by Hongbo Xu, Jundong Zhang, Jiale Liu, Yang Cao, Ao Ma

“…To address the impact of load variations, external environmental changes, and the tuning of the parameters on Permanent Magnet Synchronous Motors (PMSMs) used in ships, this study proposes an Active Disturbance Rejection Control (ADRC) strategy for PMSMs, optimized by the Quantum-behaved Particle Swarm Optimization (QPSO) algorithm. First, based on the PMSM model, the study addresses the limited disturbance rejection capability of the traditional fal function in the Extended State Observer (ESO) of conventional ADRC. …”
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Prediction and Mapping of Soil Total Nitrogen Using GF-5 Image Based on Machine Learning Optimization Modeling by LIU Liqi, WEI Guangyuan, ZHOU Ping

“…Three machine learning algorithms were introduced: Partial least squares regression (PLSR), backpropagation neural network (BPNN), and support vector machine (SVM) driven by a polynomial kernel function (Poly). …”
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Prediction of Shear Strength of Steel Fiber-Reinforced Concrete Beams with Stirrups Using Hybrid Machine Learning and Deep Learning Models by B. R. Kavya, A. S. Shrikanth, K. S. Sreekeshava

“…In the present research effort, a hybrid support vector regression model combined with a particle swarm optimization algorithm is provided, to explore the relationship between the material and dimensional characteristics of a concrete beam and its shear strength. …”
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Multi-fault Repair and Optimization Strategy of Distribution Network Based on Fault Adjacency State by Aiqing YU, Liqing DING, Yufei WANG, Hao LI

“…During the reconstruction calculation period, the node voltage based adaptive ordered ring matrix for the ring network is set up as the solution space of the algorithm. Then, the Levy coefficient quantum particle swarm optimization was applied using the decreasing cosine function and Levy flight to improve the quantum particle swarm optimization algorithm. …”
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Generation of shortest path search dataflow networks of actors for parallel multi-core implementation by A. A. Prihozhy

“…The objective is to improve performance of parallel implementations of algorithms which have the property of partial order of computations on multicore processors.Methods. …”
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