Intelligent ESG portfolio optimization: A multi-objective AI-driven framework for sustainable investments in the Indian stock market by Apurv Gaurav, Kripamay Baishnab, Piyush Kumar Singh

“…In the second stage, portfolio allocation is optimized by balancing risk, return, and ESG scores using the Non-dominated Sorting Genetic (NSG) algorithm. …”
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Toward a linear-ramp QAOA protocol: evidence of a scaling advantage in solving some combinatorial optimization problems by J. A. Montañez-Barrera, Kristel Michielsen

“…Abstract The quantum approximate optimization algorithm (QAOA) is a promising algorithm for solving combinatorial optimization problems (COPs), with performance governed by variational parameters $${\{{\gamma }_{i},{\beta }_{i}\}}_{i = 0}^{p-1}$$ { γ i , β i } i = 0 p − 1 . …”
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Heterogeneous Graph Neural-Network-Based Scheduling Optimization for Multi-Product and Variable-Batch Production in Flexible Job Shops by Yuxin Peng, Youlong Lyu, Jie Zhang, Ying Chu

“…Moreover, the Proximal Policy Optimization (PPO) algorithm is leveraged to achieve end-to-end optimization of scheduling decisions. …”
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Network Optimization of Fresh Products Cold Chain Considering Supply Disruption and Demand Fluctuation Under the Dual-Carbon Policy by Haojie Ran, Dichen He, Huajun Tang

“…This study focuses on introducing the key optimization goals of the cold chain network for fresh products: maximizing the service level while minimizing operating costs and carbon emissions. …”
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Analysis of Regional Spatial Characteristics and Optimization of Tourism Routes Based on Point Cloud Data from Unmanned Aerial Vehicles by Yu Chen, Hui Zhong, Jianglong Yu

“…Using this three-dimensional map of spatial features, we explored tourist routes in complex environments and applied an improved particle swarm optimization algorithm to identify optimal tourist routes characterized by safety, smoothness, and feasibility. …”
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The Optimization Design of Sub-Regions Scanning and Vibration Analysis for Beaconless Spatial Acquisition in the Inter-Satellite Laser Communication System by Yunjie Teng, Min Zhang, Shoufeng Tong

“…We mainly report an efficient approach to optimize the design of beaconless spatial laser acquisition. …”
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Study on multi-parameter optimization of seismic isolation bearings for continuous girder bridges considering interactions among key parameters by Zhaolan Wei, Bowen Yang, Qixuan You, Konstantinos Daniel Tsavdaridis, Shaomin Jia

“…First, using a conventional particle swarm optimization (PSO) algorithm, the individual and combined effects of each parameter on key response indicators are identified. …”
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An efficient binary Harris hawks optimization based on logical operators for wind turbine layout according to various wind scenarios by Ayşe Beşkirli

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Prediction of carbon dioxide emissions from Atlantic Canadian potato fields using advanced hybridized machine learning algorithms – Nexus of field data and modelling by Muhammad Hassan, Khabat Khosravi, Aitazaz A. Farooque, Travis J. Esau, Alaba Boluwade, Rehan Sadiq

“…In this study, three novel machine learning algorithms of additive regression-random forest (AR-RF), Iterative Classifier Optimizer (ICO-AR-RF), and multi-scheme (MS-RF) were explored for carbon dioxide (CO2) flux rate prediction from three agricultural fields. …”
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Predicting Rolling Element Bearings’ Deterioration Vibration Trend based on Limited Historical Data for a Desired Confidence Level using Machine Learning Algorithms by Mohammad Reza Seif, Somaye Mohammadi, Parham Rahimi, Mehdi Behzad

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Adaptive polarimetric optimization for ground deformation monitoring using multi-temporal InSAR with dual-polarization sentinel-1 by Leixin Zhang, Feng Zhao, Yunjia Wang, Jordi J. Mallorqui, Teng Wang, Yuxuan Zhang, Zhongbo Hu, Sen Du, José Fernández

“…Additionally, it demonstrates enhanced ground deformation monitoring accuracy, as evidenced by a lower average RMSE compared to the VV and minimum mean square error (MMSE) methods when comparing against GPS data. While achieving a nearly equivalent number of monitoring pixels as the optimal exhaustive search polarimetric optimization (ESPO) algorithm, ADCMD-PolMTI operates 235 and 13 times faster for PSs and DSs, respectively. …”
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Advancing flood susceptibility prediction: A comparative assessment and scalability analysis of machine learning algorithms via artificial intelligence in high‐risk regions of Paki... by Mirza Waleed, Muhammad Sajjad

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Localization of Sensor Nodes in 3D Wireless Sensor Networks with a Single Anchor by an Improved Adaptive Artificial Bee Colony (iaABC) Algorithm by Dursun Ekmekci, Hüseyin Altınkaya

“…The method employs the Improved Adaptive Artificial Bee Colony (iaABC) algorithm, a model of the classical ABC algorithm. …”
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Hippopotamus based optimization for reliable and cost-effective designing of stand-alone hybrid renewable system for a remote area by Sanjeev Gupta, Sanjeev Gupta, Yashwant Sawle, Kishor Thakre, M. Thirunavukkarasu, M. Thirunavukkarasu

“…In this study, metaheuristic optimization approaches that have recently been constructed, which include the coati optimization algorithm and hippopotamus optimization, were applied to determine the perfect dimensions for a grid-independent composite renewable energy infrastructure. …”
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Sensitivity Analysis for Dynamic Parameters of High–Speed Train Based on Multimodal–Optimization Improved Kriging Model and Distance Correlation by Jie JIANG, Xufeng YANG, Guofu DING

“…Contrasting with traditional single-objective intelligent optimization algorithms, the algorithm presented here transforms a single-objective optimization problem into a double-objective optimization problem by introducing the population-diversity index. …”
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Hybrid-driven modeling using a BiLSTM–AdaBoost algorithm for diameter prediction in the constant diameter stage of Czochralski silicon single crystals by Yu-Yu Liu, Ding Liu, Shi-Hai Wu, Yi-Ming Jing

“…Subsequently, the prediction results of the BiLSTM network are weighted and fused by the AdaBoost algorithm to obtain the final time series prediction output, and the prediction performance is further enhanced by iterative optimization. …”
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An adaptive prediction method for ultra-short-term generation power of power system based on the improved long- and short-term memory network of sparrow algorithm by Peipei Yang, Zhidong Chen, Wen Tang, Zongyang Liu, Bingrui He

“…The methodology involves the following steps: (1) Collecting historical ultra-short-term power generation data from photovoltaic systems, where outlier detection and data cleaning are performed using horizontal processing methods; (2) Applying Pearson correlation analysis to identify key meteorological factors significantly influencing power output as feature inputs; (3) Developing an Adaptive Sparrow Search Algorithm (ASSA) by dynamically adjusting the quantities of discoverers and followers in traditional SSA; (4) Optimizing LSTM network parameters through ASSA to enhance prediction accuracy. …”
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The SADRA Algorithm as a Framework for Sustainable Innovation: A Review of Case Studies on 3D‐Printed Reinforced Concrete Beam and Fiber‐Reinforced Concrete by Mohammad Hematibahar, Makhmud Kharun, Abhijit Bhowmik, Valentin Romanovski

“…The effectiveness of this algorithm is demonstrated through two comparative case studies: 3D‐Printed Reinforced Concrete Beams and Fiber‐Reinforced Concrete. …”
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Hybrid vegetation-seawall coastal systems for wave hazard reduction: analytics for cost-effective design from optimized features by Erfan Amini, Reza Marsooli, Somayeh Moazeni, Bilal M. Ayyub

“…This study develops a novel framework combining a non-hydrostatic wave model, a data-driven surrogate model, and a multi-objective optimization algorithm to optimize hybrid designs. Results demonstrate that vegetation integration significantly reduces wave impacts, enhancing seawall performance. …”
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Lightweight and rapid adaptive super-resolution interpolation reconstruction algorithm for super-pixel segmentation of super-wide field-of-view long-wave infrared images by Dongdong Shi, Xia Cai, Limin Liu, Fuyu Huang, Kangli Xu, Yuanbo Wang, Yudan Chen

“…Evaluation of the reconstructed images following a 2× reconstruction of dataset 1 reveals that the energy of gradient function of the proposed algorithm exhibits a 21.93% improvement compared to the sub-optimal algorithm. …”
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