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3001
Two-layer multi-objective optimal sizing of electric-hydrogen energy storage with the integration of extreme scenario generation and preference-information decision-making
Published 2025-09-01“…Furthermore, an angle preference-based multi-objective particle swarm optimization algorithm is introduced to incorporate the preferences of decision-makers and yield flexible and tailored optimal sizing solutions. …”
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3002
A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems
Published 2025-06-01“…To overcome these challenges, this paper presents ORA-DL (Optimized Resource Allocation using Deep Learning) an advanced framework that integrates deep learning, Internet of Things (IoT)-based sensing, and real-time adaptive control to optimize smart grid energy management. …”
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3003
Parametric Optimization and Assessment of Modern Heritage Shading Screen for a Mid-Rise Building in Arid Climate: Modernizing Traditional Designs
Published 2025-04-01“…This research explores how parametric design and optimization based on genetic algorithms (GAs) can improve shading structures to reduce solar radiation and lower cooling energy consumption. …”
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3004
A machine learning model with crude estimation of property strategy for performance prediction of perovskite solar cells based on process optimization
Published 2024-12-01“…Nine machine learning algorithms, including decision tree (DT), random forest (RF), CatBoost, LassoLarsCV, histogram gradient boosting, extreme gradient boosting (XGBoost), K nearest neighbor, ridge regression (Ridge), and linear regression (Linear R), were employed to optimize PSC preparation and assess its impact on device performance. …”
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3005
An Optimal Internet of Things-Driven Intelligent Decision-Making System for Real-Time Fishpond Water Quality Monitoring and Species Survival
Published 2024-12-01“…Our framework’s capability to manage complex, multi-species fishpond environments was validated across diverse setups, showcasing its potential to transform fish farming practices by ensuring sustainable climate-adaptive management through real-time water quality optimization. This study marks a significant step forward in climate-smart aquaculture, contributing to enhanced fish health, survival, and yield while mitigating the risks posed by climate change on aquatic ecosystems.…”
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3006
Co‐Creation in Automated Public Space Lighting Design: Enhancing Safety and Reducing Light Pollution
Published 2025-05-01“…The article presents an algorithm that iteratively determines the optimal number and placement of lamps based on expected lighting levels. …”
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3007
A source-load collaborative stochastic optimization method considering the electricity price uncertainty and industrial load peak regulation compensation benefit
Published 2025-06-01“…This paper combines the complete ensemble empirical mode decomposition adaptive noise (CEEMDAN), whale optimization algorithm (WOA), and long short-term memory network (LSTM) to propose a CEEMDAN-WOA-LSTM prediction model for electricity price scenarios. …”
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3008
Enhancing cold storage efficiency: Continuous deep deterministic policy gradient approach to energy optimization utilizing strategic sensor input data
Published 2025-04-01“…In this study, we present a continuous Deep Deterministic Policy Gradient (DDPG)-based control algorithm applied to extended-scale cold storage environments to optimize energy efficiency. …”
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3009
Programming and Setting Up the Object Detection Algorithm YOLO to Determine Feeding Activities of Beef Cattle: A Comparison between YOLOv8m and YOLOv10m
Published 2024-09-01“…YOLOv10 outperformed YOLOv8 with slightly higher precision, recall, mAP50, and mAP50-95 scores. Although both algorithms demonstrated similar overall accuracy (around 90%), YOLOv8 reached optimal training faster and exhibited less overfitting. …”
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3010
A comparative study of machine learning algorithms for fall detection in technology-based healthcare system: Analyzing SVM, KNN, decision tree, random forest, LSTM, and CNN
Published 2025-01-01“…The results show that CNN and LSTM deliver the best performance with accuracies of 94% and 92%, while Random Forest offers a good balance between accuracy and processing time. …”
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3011
Impact of integrating type-1 distributed generation on distribution network using modified genetic algorithm and voltage stability index: a technical and cost–benefit analysis appr...
Published 2024-12-01“…The backward-forward sweep formed the backbone of the load flow, while the voltage stability index was used to select the suitable buses where type-1 DG was integrated for optimal performance. …”
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3012
Enhancing Fracture Detection in Remote Settings: Evaluating the Efficacy of FIXUS AI Deep Learning Algorithms in Identifying Fifth Metatarsal Fractures Using Mixed-Quality X-rays
Published 2024-12-01“…Category: Midfoot/Forefoot; Trauma Introduction/Purpose: The diagnosis of fractures can be challenging in specific medical settings due to limited expertise or time. While deep learning has shown promising results, its use is confined to the quality of images and the hassle of importing images to the models. …”
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3013
Enhancing Intelligent Control Strategies for UAVs: A Comparative Analysis of Fuzzy Logic, Fuzzy PID, and GA-Optimized Fuzzy PID Controllers
Published 2025-01-01“…The GAFPID controller employs evolutionary computation through a genetic algorithm to optimize parameter tuning, offering superior control performance. …”
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3014
AI based data-driven point cloud optimization strategy in cloud computing framework for improving rendering performance of virtual city scenes
Published 2025-07-01“…To address the problem of poor rendering of virtual city scene, the paper proposes an Artificial Intelligence (AI) based bundle adjustment point cloud optimization model based on cross-entropy loss by combining with the multi-detail hierarchy technique, the rendering efficiency is improved while guaranteeing the high consistency between the 3D model and the real world in terms of geometry. …”
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3015
A Continuous Space Path Planning Method for Unmanned Aerial Vehicle Based on Particle Swarm Optimization-Enhanced Deep Q-Network
Published 2025-02-01“…To address this issue, we introduce the particle swarm optimization (PSO) algorithm into DQN to convert the discrete action space into a continuous one. …”
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3016
Energy storage configuration considering user-shared costs in peak shaving auxiliary services with improved multi-objective particle swarm optimization
Published 2025-04-01“…Moreover, an improved particle swarm optimization algorithm, specifically adapted for this model, is developed. …”
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3017
Application of a grey wolf optimization-enhanced convolutional neural network and bidirectional gated recurrent unit model for credit scoring prediction.
Published 2025-01-01“…The GWO algorithm is introduced to further improve the overall performance of the model by optimizing key parameters. …”
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3018
Spatially optimized allocation of water and land resources based on multi-dimensional coupling of water quantity, quality, efficiency, carbon, food, and ecology
Published 2025-03-01“…The optimization results indicate that the irrigated area of rice increased by 0.04–6.08 %, while the irrigated area for corn decreased by 6.20–0.02 %, with the overall irrigated area remaining relatively stable. …”
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3019
Multi-Objective Ore Blending Optimization for Polymetallic Open-Pit Mines Based on Improved Matter-Element Extension Model and NSGA-II
Published 2025-05-01“…This study constructs a multi-objective ore blending optimization system for complex polymetallic open-pit mines based on the improved matter-element extension model and NSGA-II algorithm. …”
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3020
Nonlinear Compensation of the Linear Variable Differential Transducer Using an Advanced Snake Optimization Integrated with Tangential Functional Link Artificial Neural Network
Published 2025-02-01“…First, the Latin hypercube sampling method and the Levy flight method are introduced into the snake optimization (SO) algorithm, which enhances the global search ability and diversity preservation ability of the SO algorithm and effectively solves the common overfitting and local optimal problems in the training process of the gradient descent method. …”
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