Optimizing guest experience in smart hospitality: Integrated fuzzy-AHP and machine learning for centralized hotel operations with IoT by Sinan Andan Diwan

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On the Use of Azimuth Cutoff for Sea Surface Wind Speed Retrieval From SAR by Yuting Zhu, Giuseppe Grieco, Jiarong Lin, Marcos Portabella, Xiaoqing Wang

“…The methodology probabilistically combines SAR data with ancillary meteorological information and optimizes the retrieval process through a cost function that leverages the sensitivity of the azimuth cutoff to changes in wind vector fields. …”
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Neural network inspired efficient scalable task scheduling for cloud infrastructure by Punit Gupta, Arnaav Anand, Pratyush Agarwal, Gavin McArdle

“…In this work, we aim to use the Harmony Search Algorithm and neural networks to create a fault aware system for optimal usage of cloud resources. …”
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Parametric Optimization of Train Brake Pad Using Reverse Engineering with Digital Photogrammetry 3D Modeling Method by P Paryanto, Muhammad Faizin, R Rusnaldy

“…This was followed by processing 2D images using Agisoft Metashape 2.2.1 software and Artificial Intelligence (AI) algorithms to create a precise 3D model. Subsequently, assessment was performed using feasibility in terms of cost, time, and accuracy. …”
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Intelligent Optimized Combined Model Based on GARCH and SVM for Forecasting Electricity Price of New South Wales, Australia by Yi Yang, Yao Dong, Yanhua Chen, Caihong Li

“…In this paper, we propose an optimized combined forecasting model by ant colony optimization algorithm (ACO) based on the generalized autoregressive conditional heteroskedasticity (GARCH) model and support vector machine (SVM) to improve the forecasting accuracy. …”
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A Method for Quantifying Mung Bean Field Planting Layouts Using UAV Images and an Improved YOLOv8-obb Model by Kun Yang, Xiaohua Sun, Ruofan Li, Zhenxue He, Xinxin Wang, Chao Wang, Bin Wang, Fushun Wang, Hongquan Liu

“…The results indicated that on the 13th day post seeding, a 2640 × 1978 image captured at 7 m above ground level exhibited optimal detection performance. Compared with YOLOv8, YOLOv8-obb, YOLOv9, and YOLOv10, the YOLOv8-obb-p2 model improved precision by 1.6%, 0.1%, 0.3%, and 2%, respectively, and F1 scores improved by 2.8%, 0.5%, 0.5%, and 3%, respectively. …”
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Solving Action Semantic Conflict in Physically Heterogeneous Multi-Agent Reinforcement Learning with Generalized Action-Prediction Optimization by Xiaoyang Yu, Youfang Lin, Shuo Wang, Sheng Han

“…Conversely, completely independent agent parameters significantly escalate computational costs and training complexity. To address these challenges, we introduce an adaptive MARL algorithm named Generalized Action-Prediction Optimization (GAPO). …”
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Advancement of electric vehicle technologies, classification of charging methodologies, and optimization strategies for sustainable development - A comprehensive review by Vikram Goud Madaram, Pabitra Kumar Biswas, Chiranjit Sain, Sudhakar Babu Thanikanti, Praveen Kumar Balachandran

“…The review evaluates algorithms and mathematical models that maximize efficiency, reduce costs, and improve charging resource accessibility. …”
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Multi-objective optimization of EMS facilities using multi-source data: A case study in Dangtu, China by Jinze Li, Xiao Wang, Qiyan Zhang, Peng Tang

“…A multi-objective evolutionary algorithm calculates Pareto optimal solutions for site selection, allowing for a balanced consideration of conflicting EMS siting objectives. …”
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A Distributed Economic Power Dispatch Strategy Considering State of Charge for Microgrids by Kaicheng Lu, Shufeng Dong, Yonghua Song

“…Every node estimates the average SoC of all battery energy storage systems(BESSs) in a microgrid and determines the power of the local BESS and microturbine (MT) autonomously to achieve SoC balancing and economic dispatch with component constraints and power balance constraints by peer-to-peer communication with its neighbors. To improve the effectiveness of power distribution, an improved average consensus algorithm(IACA) based on particle swarm optimization (PSO) is proposed to adjust the weight matrix of communication networks, which reduces the number of iterations to estimate the average SoC. …”
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An Optimal Sizing Methodology for a Wind/PV Hybrid Energy Production System for Agricultural Irrigation in Skikda, Algeria by Nadhir Abderrahmane, Allaoua Brahmia, Adlen Kerboua, Ridha Kelaiaia

“…The optimization algorithm used was tailored to the formulated problem, ensuring reliable and applicable results. …”
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Modified invasive weed optimization MPPT approach for PV system interfaced with BLDC motor for water pumping system by S. Nagaraja Rao, B. M. Kiran Kumar, B. M. Manjunatha, A. Suresh Kumar

“…Therefore, the modified invasive weed optimization (MIWO) approach integrated with P&O approach to improve performance under PSC. …”
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Allocation of Interline Power Flow Controller-Based Congestion Management in Deregulated Power System by Muhammad Safdar Sial, Qinghua Fu, Talles Vianna Brugni

“…The present paper provides an optimal location of the Interline Power Flow Controller (IPFC) method in the power system using the Sperm Whales Swarm Optimization (SWSO) algorithm. …”
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E-Commerce Logistics Software Package Tracking and Route Planning and Optimization System of Embedded Technology Based on the Intelligent Era by Dan Zhang, Zhiyang Jia

“…To sum up, this algorithm could effectively optimize the distribution route of logistics packages and improve the efficiency of package transportation.…”
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Optimizing High-Speed Railroad Timetable with Passenger and Station Service Demands: A Case Study in the Wuhan-Guangzhou Corridor by Jin Wang, Leishan Zhou, Yixiang Yue, Jinjin Tang, Zixi Bai

“…The results show that the proposed model and algorithm can quickly reduce the defined cost function by 38.2% and improve the average travel speed by 10.7 km/h, which indicates that our proposed model and algorithm can effectively improve the quality of a constructed train timetable and the travel efficiency for passengers.…”
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Optimizing microgrid performance a multi-objective strategy for integrated energy management with hybrid sources and demand response by Mohsen Moosavi, Javad Olamaei, Hossein Mohmmadnezhad Shourkaei

“…When compared to leading optimization algorithms, the proposed approach showed better performance. …”
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Research on the optimal scheduling of a multi-storage combined integrated energy system based on an energy supply grading strategy by Na Zhang, Feng You, Bingqian Hu, Jingyu Li, Guangchen Liu

“…Next, considering the system operational cost and carbon emission cost as the optimization goal, a comprehensive energy optimization scheduling model of multi-storage combined hierarchical energy supply is constructed. …”
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Co-Optimization Operation of Distribution Network-Containing Shared Energy Storage Multi-Microgrids Based on Multi-Body Game by Hao Wu, Ge Cao, Rong Jia, Yan Liang

“…Finally, based on the power interaction of microgrids to measure their contributions, an improved Shapley value cost allocation method is proposed, effectively achieving a balanced distribution of benefits among the distribution network, shared energy storage, and multi-microgrids, thereby improving overall operational revenue. …”
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Next generation network resource allocation method based on cooperative game and decision-making in advance by RAO Xiang, ZHANG Shun-yi, SUN Yan-fei, DING Wen-tao

“…It’s an important way to guarantee QoS for the next generation network（NGN） with diverse services by allo-cating resources reasonably and optimizing the efficiency of whole network according to diverse service styles.A net-work resource allocating method based on co-operative game theory for NGN was proposed and analyzed,and it had a weakness which brought about overgreat system costing.In order to overcome this weakness,an idea about deci-sion-making in advance was added,and an improved resource allocation algorithm was proposed,which could guarantee the efficiency of whole network best and reduce the system costing.Simulation results of this method show its validity.…”
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Enhancing microgrid forecasting accuracy with a TCNN-TLS framework: A novel approach to mitigating uncertainty in renewable energy and load predictions by Md. Omer Faruque, Md. Majharul Islam, Md Jakaria Talukder, Arif Mia, Shahriar Tasnim, Md. Alamgir Hossain, S.M. Muyeen

“…The employed settings contain a temporal convolutional neural network (TCNN) optimized with a pelican optimization algorithm (POA) to enhance its hyper-parameter selection. …”
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