Optimizing integration techniques for UAS and satellite image data in precision agriculture — a review by Aliasghar Bazrafkan, C. Igathinathane, Nonoy Bandillo, Paulo Flores

“…This review explores the significance of integrating high-resolution UAS and satellite imagery via pixel-based, feature-based, and decision-based fusion methods. The study investigates optimization techniques, spectral synergy, temporal strategies, and challenges in data fusion, presenting transformative insights such as enhanced biomass estimation through UAS-satellite synergy, improved nitrogen stress detection in maize, and refined crop type mapping using multi-temporal fusion. …”
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APPLICATION OF MATHEMATICAL MODELING OF THE AIRCRAFT STRUCTURES STRESS STATE TO OPTIMIZE CORROSION DAMAGE REMOVAL by D. P. Saidzhanov, V. V. Efimov

“…However, it is impossible to refuse the removal of corrosion damage, but it is possible to optimize the stripping area parameters. The purpose of this paper is to solve the problem by applying mathematical modeling of the aircraft structures stress state by using open source software based on a finite element method (FEM). …”
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Search direction optimization of power flow analysis based on physics-informed deep learning by Baoliang Li, Qiuwei Wu, Yongji Cao, Changgang Li

“…Power flow analysis is crucial for obtaining power system operation states and optimizing control measures. The increasing integration of renewable energy sources has resulted in a more complex power system, posing challenges to the computational efficiency and convergence of conventional power analysis methods. …”
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Sunflower-based butterfly optimization algorithm with enhanced RNN for the harmonics elimination in multilevel inverter by V. Mohan, G. Krithiga, M. Thamil Alagan, V. Sathya

“…In this paper, the Sunflower based– Butterfly Optimization Algorithm (SF-BOA) is presented as a method for evaluating transcendental nonlinear equations using an MLI in a SHE approaches. …”
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Auto regressive neural network-driven reliability optimization in base-isolated building design by John Thedy, Kuo-Wei Liao, Taeyong Kim

“…Trained on various ground motions and Nonlinear Time History Analysis (NLTHA) data, the ARNN produces full response histories, unlike prior methods focused solely on peak responses. A Single Degree of Freedom (SDOF) example demonstrates ARNN accuracy, and a four-story base-isolated building is used for a Reliability-Based Design Optimization (RBDO) case study. …”
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A GD-PSO Algorithm for Smart Transportation Supply Chain ABS Portfolio Optimization by Yingjia Sun, Hongfeng Ren

“…Different from forward selection or linear optimization, which could have low efficiency for complicated problems with large sample size and multiple objectives, new methods and algorithms for NP-hard problems would be necessary to be investigated. …”
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Dam Risk Identification Method Based on EAHP-EWM-TOPSIS by ZHAN Mingqiang, CHEN Bo, TIAN Jufei, HU Zelin, PAN Xinmei

“…To address the uncertainty and fuzziness of dam risk indicators, this paper proposes a dam risk identification model based on the EAHP-EWM-TOPSIS game combination model.This is to determine the subjective and objective weights of risk evaluation indicators by extension analytic hierarchy process and entropy weight method respectively.Meanwhile, the game theory is introduced to determine the optimal combination weight, and a weighted standardized decision matrix is constructed.Then, the TOPSIS method is employed to calculate the relative proximity between each risk factor and the ideal solution as the basis for ranking risk factors to identify the main risk sources of dams.The engineering example shows that the main risk factors affecting the safe service of the dams are dam seepage and cross-bank seepage, with the relative proximity of 0.712 7 and 0.855 2 respectively.The identified main risk factors are consistent with the actual engineering situation, which verifies the model effectiveness.The differentiation degree of this model is more obvious than other models, providing an effective basis for dam reinforcement and risk management.…”
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The Application of Graph Neural Networks in Power Systems from Perspective of Perception-Prediction-Optimization by Zhuo LI, Yinzhe WANG, Lin YE, Yadi LUO, Xuri SONG, Zhenyu ZHANG

“…Conventional data analysis methods for Euclidean space often exhibit poor performance and low accuracy when representing the topological structures relationship with multi-source heterogeneous and irregular characteristics. …”
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Reinforcement Learning for Optimizing Renewable Energy Utilization in Buildings: A Review on Applications and Innovations by Panagiotis Michailidis, Iakovos Michailidis, Elias Kosmatopoulos

“…The integration of renewable energy systems into modern buildings is essential for enhancing energy efficiency, reducing carbon footprints, and advancing intelligent energy management. However, optimizing RES operations within building energy management systems introduces significant complexity, requiring advanced control strategies. …”
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Research on optimization technology of new pipeline design for regional natural gas pipeline network by Jingyi CUI, Kunfeng ZHU, Cuixian GAO, Li GU, Jing REN, Yuxing LI, Wuchang WANG

“…To meet future gas demand and enhance the efficiency of pipeline design, it is essential to review and analyze existing pipeline planning and design methods, as well as optimization algorithms. There is an urgent need to develop a set of design optimization methods suitable for complex pipeline network systems with multiple gas sources, numerous users, and aging pipeline infrastructures. …”
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Development and Optimization of a Novel Deep Learning Model for Diagnosis of Quince Leaf Diseases by A. Naderi Beni, H. Bagherpour, J. Amiri Parian

“…Today, deep convolutional neural networks (DCNNs), a novel approach to image classification, have become the most crucial detection method. DCNNs improve detection or classification accuracy by developing machine-learning models with many hidden layers to extract optimal features. …”
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Chance-constrained optimal schedule of battery energy storage considering the uncertainties of renewable generation by Zhi Li, Dawei Xie, Haifeng Ye, Yujun Li, Jinzhong Li, Yichi Chen, Yue Yang

“…Since renewable energy generation has strong uncertainties and pure conventional unit dispatch schemes are limited by the unit-operating capacities, such scheduling is inapplicable for power systems with high proportions of renewable energy sources (RESs). We propose an optimal scheduling model for battery energy storage systems (BESSs) by considering the uncertainties of RESs. …”
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Coal pulverization by electric pulse method for water-coal fuel by Б.Р. Нусупбеков, А.К. Хасенов, Д.Ж. Карабекова, У.Б. Нусупбеков, М. Стоев, М.М. Болатбекова

“… In the article describes the electrohydraulic method as a source of high energy concentration for the disintegration of the components of water-coal fuel in an aqueous medium under the action of pulsed discharges. …”
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Optimization of the encapsulation of arazá pulp by spray drying: Physicochemical, morphological and in vitro digestion studies by Greilis Quintero-Gamero, Francis S. Sánchez-Garzón, Aureliano Rodríguez-Cortina, María Hernández-Carrión, Luz Stella Nerio

“…This study presents an optimized method to obtain microencapsulates from arazá pulp (not obtained before), with a great potential for the development of functional foods.…”
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TMBocelot: an omnibus statistical control model optimizing the TMB thresholds with systematic measurement errors by Xin Lai, Shaoliang Wang, Xuanping Zhang, Xiaoyan Zhu, Yuqian Liu, Zhili Chang, Zhili Chang, Xiaonan Wang, Xiaonan Wang, Yang Shao, Yang Shao, Jiayin Wang, Yixuan Wang

“…Given the unavoidable errors with current technologies, it is essential to adopt modeling methods to determine the optimal TMB-positive threshold. …”
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A Trusted Federated Learning Method Based on Consortium Blockchain by Xiaojun Yin, Xijun Wu, Xinming Zhang

“…Federated learning (FL) has gained significant attention in distributed machine learning due to its ability to protect data privacy while enabling model training across decentralized data sources. However, traditional FL methods face challenges in ensuring trust, security, and efficiency, particularly in heterogeneous environments with varying computational capacities. …”
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Multi-Objective Majority–Minority Cellular Automata Algorithm for Global and Engineering Design Optimization by Juan Carlos Seck-Tuoh-Mora, Ulises Hernandez-Hurtado, Joselito Medina-Marín, Norberto Hernández-Romero, Liliana Lizárraga-Mendiola

“…When dealing with complex models in real situations, many optimization problems require the use of more than one objective function to adequately represent the relevant characteristics of the system under consideration. …”
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SYNTHESIS AND OPTIMIZATION OF CARBON NANOPARTICLES (C-DOTS) AS ABSORBER MATERIALS FOR SOLAR DISTILLATION APPLICATIONS by B. W. Nuryadin, U. Qulsum, E. C. S. Mahen, A. Y. Nuryantini, H. Aliah, Y. S. Perkasa

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Optimization of extraction and enrichment process of cannabidiol from industrial hemp and evaluation of its bioactivity by Junkai Wu, Xiaomeng Zhang, Xiaoqing Liu, Zunlai Sheng, Zunlai Sheng, Jianping Hu, Feiyan Zhang

“…., a perennial dioecious herb renowned for its industrial applications, serves as the source of hemp. Cannabidiol (CBD), a non-psychotropic compound derived from industrial hemp, has garnered considerable interest due to its promising therapeutic potential.MethodsThe extraction parameters for CBD from industrial hemp were optimized using the Box-Behnken design and response surface methodology (RSM). …”
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Advanced Financial Fraud Malware Detection Method in the Android Environment by Jaeho Shin, Daehyun Kim, Kyungho Lee

“…Five ML algorithms were used to evaluate the proposed approach, and the optimal hyperparameter values for each algorithm were obtained using a grid search method. …”
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