A deep learning and IoT-driven framework for real-time adaptive resource allocation and grid optimization in smart energy systems by Arvind R. Singh, M. S. Sujatha, Akshay D. Kadu, Mohit Bajaj, Hailu Kendie Addis, Kota Sarada

“…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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A machine learning model with crude estimation of property strategy for performance prediction of perovskite solar cells based on process optimization by Dan Li, Ernie Che Mid, Shafriza Nisha Basah, Xiaochun Liu, Jian Tang, Hongyan Cui, Huilong Su, Qianliang Xiao, Shiyin Gong

“…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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An Optimal Internet of Things-Driven Intelligent Decision-Making System for Real-Time Fishpond Water Quality Monitoring and Species Survival by Saima Kanwal, Muhammad Abdullah, Sahil Kumar, Saqib Arshad, Muhammad Shahroz, Dawei Zhang, Dileep Kumar

“…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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Calculation of economic velocity in supercritical CO2 transport pipelines by Yuhan CHENG, Changjun LI, Wenlong JIA, Qian GAO, Shixiong FU, Wenqin ZHANG

“…ObjectiveCarbon Capture, Utilization and Storage (CCUS) is widely recognized as a leading solution for reducing greenhouse gas emissions, while pipeline transport is the optimal method for large-scale, long-distance CO2 transport. …”
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The Influence of Three Parent Crossbreeding on the Dual Population Genetic Algortihm by Esra'a Alkafaween, Obada Alhabashneh, Maram M. Al-Mjali

“…A genetic algorithm (GA) is an optimization technique based on natural genetics, using selection, crossover, and mutation. …”
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Assessment of Solar Energy Generation Toward Net-Zero Energy Buildings by Rayan Khalil, Guilherme Vieira Hollweg, Akhtar Hussain, Wencong Su, Van-Hai Bui

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The Fine Feature Extraction and Attention Re-Embedding Model Based on the Swin Transformer for Pavement Damage Classification by Shizheng Zhang, Kunpeng Wang, Zhihao Liu, Min Huang, Sheng Huang

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Enhancing cold storage efficiency: Continuous deep deterministic policy gradient approach to energy optimization utilizing strategic sensor input data by Jong-Whi Park, Young-Min Ju, Hak-Sung Kim

“…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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Programming and Setting Up the Object Detection Algorithm YOLO to Determine Feeding Activities of Beef Cattle: A Comparison between YOLOv8m and YOLOv10m by Pablo Guarnido-Lopez, John-Fredy Ramirez-Agudelo, Emmanuel Denimal, Mohammed Benaouda

“…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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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 by Afuan Lasmedi, Isnanto R. Rizal

“…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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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... by Olakunle Elijah Olabode, Daniel Oluwaseun Akinyele, Titus Oluwasuji Ajewole, Samuel Okeolu Omogoye, Akeem Abimbola Raji

“…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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Enhancing Consumer Agent Modeling Through Openness-Based Consumer Traits and Inverse Clustering by Brahim Benaissa, Masakazu Kobayashi, Hiroshi Takenouchi

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An Instantaneous Minimum Input Energy Control Strategy for Isolation Systems With Co-Varying Stiffness and Damping by Leilei Xia, Dehong Wu, Lu Chen, Jingjing Li

“…For such systems, an instantaneous minimum input energy (IMIE) control strategy is proposed. This algorithm explicitly establishes the functional relationship between damping and stiffness, converting the optimization problem into a single-variable search for optimal stiffness while automatically determining the corresponding optimal damping. …”
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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 by Atta Taseh MD, Alireza Gholipour PhD, Mani Eftekhari, Alireza Ebrahimi MD, Alexandra F. Flaherty MD, MS, Alexandra F. Flaherty MD, MS, Sumner Jones, Varun Nukala, Gregory R. Waryasz MD, Daniel Guss MD, MBA, John Y. Kwon MD, Christopher W. DiGiovanni MD, Lorena Bejarano-Pineda MD, Soheil Ashkani-Esfahani MD

“…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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Enhancing Intelligent Control Strategies for UAVs: A Comparative Analysis of Fuzzy Logic, Fuzzy PID, and GA-Optimized Fuzzy PID Controllers by Nigatu Wanore Madebo

“…The GAFPID controller employs evolutionary computation through a genetic algorithm to optimize parameter tuning, offering superior control performance. …”
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Inter-Object Navigation of Unmanned Aerial Vehicles to Increase the Efficiency and Accuracy of Inspection of Power Lines by Tymochko O., Fustii V., Kolesnyk G., Olizarenko S., Kalashnyk G., Kulish R., Tymoschuk O., Galinskji D.

“…Solving the problem of multi-criteria optimization of the drone team flight route planning made it possible to reduce the cost of monitoring critical infrastructure facilities while improving its efficiency and accuracy. …”
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AI based data-driven point cloud optimization strategy in cloud computing framework for improving rendering performance of virtual city scenes by Cao Zhongda

“…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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A Continuous Space Path Planning Method for Unmanned Aerial Vehicle Based on Particle Swarm Optimization-Enhanced Deep Q-Network by Le Han, Hui Zhang, Nan An

“…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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Energy storage configuration considering user-shared costs in peak shaving auxiliary services with improved multi-objective particle swarm optimization by Yiyou Xing, Jin Shen, Xinru Li

“…Moreover, an improved particle swarm optimization algorithm, specifically adapted for this model, is developed. …”
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Application of a grey wolf optimization-enhanced convolutional neural network and bidirectional gated recurrent unit model for credit scoring prediction. by Yetong Fang

“…The GWO algorithm is introduced to further improve the overall performance of the model by optimizing key parameters. …”
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