Assessment and Modeling of Green Roof System Hydrological Effectiveness in Runoff Control: A Case Study in Dublin by Mehdi Gholamnia, Payam Sajadi, Salman Khan, Srikanta Sannigrahi, Saman Ghaffarian, Himan Shahabi, Francesco Pilla

“…The comprehensive dataset enabled detailed modeling of runoff hydrograph parameters using rainfall hyetographs, which were subsequently analyzed through sophisticated machine learning algorithms. This research introduces an innovative approach by identifying the optimal combination of variables for modeling key runoff characteristics, including Water Retention Amount (WRA), Total RUnoff Volume (TRUV), Peak Runoff Discharge (PRD), and Peak Flow Reduction (PFR). …”
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Energy Demand Response in a Food-Processing Plant: A Deep Reinforcement Learning Approach by Philipp Wohlgenannt, Sebastian Hegenbart, Elias Eder, Mohan Kolhe, Peter Kepplinger

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Water Hyacinth Invasion and Management in a Tropical Hydroelectric Reservoir: Insights from Random Forest and SVM Classification by Luis Fernando Correa-Mejía, Yeison Alberto Garcés-Gómez

“…The objective of this study was to map and monitor the spatio-temporal distribution of water hyacinth in the Hidroituango reservoir in Colombia from 2018 to 2023, using Sentinel-2 satellite imagery and machine learning algorithms. The Random Forest (RF) and Support Vector Machine (SVM) algorithms were employed for image classification, and their performance was evaluated using various accuracy metrics. …”
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Risk Warning Method of Corn Cross-border Supply Chain Based on DBN-MFSVM by GE Zhen-lin

“…Then, based on the deep belief network, the high-latitude features of the data were extracted, and the change trend and correlation of risk indicators in the corn cross-border supply chain system were adaptively mined. Finally, the extracted high-dimensional features were input into the multi-class fuzzy support vector machine model for training to realize the risk classification early warning of corn cross-border supply chain. …”
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A comprehensive systematic review of intrusion detection systems: emerging techniques, challenges, and future research directions by Arjun Kumar Bose Arnob, Rajarshi Roy Chowdhury, Nusrat Alam Chaiti, Sudipta Saha, Ajoy Roy

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The Advanced Actuarial Data Science Based AI-Driven Solutions for Automated Loss Reserving Under IFRS 17 in Non-Life Insurance by Brighton Mahohoho, Charles Chimedza, Florance Matarise, Sheunesu Munyira

“…The model leverages advanced machine learning techniques to improve accuracy, efficiency, and adaptability in loss reserves, with a specific focus on inflation-adjusted frequency-severity modeling. …”
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SVR Data-Driven Optimization of Generator Leading Phase Operation Limit by Dengfeng LI, Mincai YANG, Yuming LIU, Ruilin XU, Xia YU, Zhaojiong LI

“…The improved second-order oscillation particle swarm optimization algorithm is then applied to solve the optimization model. …”
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Optimized YOLOv8 for enhanced breast tumor segmentation in ultrasound imaging by Ayman Mohamed Mostafa, Alaa S. Alaerjan, Bader Aldughayfiq, Hisham Allahem, Alshimaa Abdelraof Mahmoud, Wael Said, Hosameldeen Shabana, Mohamed Ezz

“…These results highlight the advantage of specialized model training and the potential of using advanced object detection algorithms for segmentation tasks. This research underscores the significant potential of using specialized training strategies and innovative model adaptations in medical imaging segmentation, ultimately contributing to better patient outcomes.…”
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Enhanced particle swarm optimization for feature selection in SVM-based Alzheimer’s disease diagnosis by Qian Zhang, Jinhua Sheng, Rougang Zhou, Qiao Zhang, Binbing Wang, Rong Zhang

“…In this paper, an enhanced Particle Swarm Optimization (PSO) algorithm, which integrates opposition-based Latin squares sampling initialization (OL) with dynamic inertia weights and learning factors (D), termed OLDPSO, is proposed to improve feature selection and classification within a Support Vector Machine (SVM) model for AD diagnosis using magnetic resonance imaging (MRI) data. …”
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SHERA: SHAP-Enhanced Resource Allocation for VM Scheduling and Efficient Cloud Computing by Ashwin Singh Slathia, Abhiram Sharma, P. B. Krishna, Saksham Anand, Ayush Rathi, Linda Joseph, Xiao-Zhi Gao

“…This work presents a system level integration of SHAP guided VM scheduling rather than a fundamentally new algorithm. Unlike static threshold or heuristic schedulers, our SHAP driven system adapts VM placement decisions in real time with built in interpretability. …”
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Targeted maximum likelihood based estimation for longitudinal mediation analysis by Wang Zeyi, Laan Lars van der, Petersen Maya, Gerds Thomas, Kvist Kajsa, Laan Mark van der

“…We utilize the highly adaptive lasso (HAL) and projection representations to derive new estimators (HAL-EIC) of the efficient influence curves (EICs) of longitudinal mediation problems and propose a fast one-step TMLE algorithm using HAL-EIC while preserving the asymptotic properties. …”
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Connotation and application paradigm of intelligent mining data intelligence enabling technology by FU Xiang, WANG Kai, WANG Ranfeng

“…The equipment layer relied on intelligent new coal machine equipment groups, developing equipment adaptive control and multi-machine collaborative linkage mechanisms. …”
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Self-Organizing TDMA: A Distributed Contention-Resolution MAC Protocol by Mahsa Derakhshani, Yahya Khan, Duc Tuong Nguyen, Saeedeh Parsaeefard, Atoosa Dalili Shoaei, Tho Le-Ngoc

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Analysis of the Impact and Weight of Structural Parameters on the Operating Characteristics of the Spring Operating Mechanism by Qi Long, Xu Yang, Keru Jiang, Changhong Zhang, Xiao Wang, Xiongying Duan

“…Finally, based on the influence weights, a sensitivity-adaptive particle swarm optimization algorithm was developed to optimize the spring-operated mechanism, reducing its failure probability by 16.67%, which is beneficial for the design of controlled switching algorithms.…”
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Review of Research on Artificial Intelligence-driven Joint Radar Communication by Xianmei WANG, Xiangbo LIU, Yuzheng REN, Yang LU, Haijun ZHANG

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6G virtualized beamforming: a novel framework for optimizing massive MIMO in 6G networks by Ahmed M. Alwakeel

“…Our framework employs a combination of advanced machine learning algorithms and software-defined networking to dynamically allocate beamforming resources, improving adaptability in high-density environments and optimizing signal-to-noise ratios. …”
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AI-driven automated discovery tools reveal diverse behavioral competencies of biological networks by Mayalen Etcheverry, Clément Moulin-Frier, Pierre-Yves Oudeyer, Michael Levin

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From data to nutrition: the impact of computing infrastructure and artificial intelligence by Pierpaolo Di Bitonto, Michele Magarelli, Pierfrancesco Novielli, Donato Romano, Domenico Diacono, Lorenzo de Trizio, Angelo Mariano, Claudia Zoani, Riccardo Ferrero, Alessandra Manzin, Maria De Angelis, Roberto Bellotti, Sabina Tangaro

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A survey on autonomous navigation for mobile robots: From traditional techniques to deep learning and large language models by Abderrahim Waga, Said Benhlima, Ali Bekri, Jawad Abdouni, Fatima Zahrae Saber

“…The review extends to modern metaheuristic algorithms, including genetic algorithms (GA), particle swarm optimization (PSO), and ant colony optimization (ACO). …”
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Harnessing Artificial Intelligence to Transform Education: Challenges and Opportunities by Ahma Greta, Kadriu Arbana

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