Detect Flame Fire Using Fractal Geometry in Color Digital Images by Laheeb Ibrahim, Khalil Alsaif, Hasan Alnima

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Adaptive Dynamic Programming with Reinforcement Learning on Optimization of Flight Departure Scheduling by Hong Liu, Song Li, Fang Sun, Wei Fan, Wai-Hung Ip, Kai-Leung Yung

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Multistage reliability-constrained stochastic planning of diamond distribution network: An approximate dynamic programming approach by Zhi Wu, Ao Li, Qirun Sun, Shu Zheng, Jingtao Zhao, Pengxiang Liu, Wei Gu

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Sequence-Information Recognition Method Based on Integrated mDTW by Boliang Sun, Chao Chen

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A Simulated Annealing Methodology to Multiproduct Capacitated Facility Location with Stochastic Demand by Jin Qin, Hui Xiang, Yong Ye, Linglin Ni

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MPMFFT based DCA-DBT integrated probabilistic model for face expression classification by Kapil Juneja

“…To acquire the features, three local region extraction models are used on both broad and responsive facial areas. …”
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A multi-agent reinforcement learning approach for continuous battery cell-level balancing by Yasaman Tavakol-Moghaddam, Mehrdad Boroushaki

“…Trained with the trust region policy optimization (TRPO) algorithm, the approach ensures stability and partial observability. …”
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Multi-Agent Optimizing Traffic Light Signals Using Deep Reinforcement Learning by Zahra Fereidooni, Luciano Alessandro Ipsaro Palesi, Paolo Nesi

“…Deep Reinforcement Learning (DRL) has emerged as a promising approach to sequential decision-making, offering adaptive and efficient solutions for traffic management. …”
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Adaptive Filtering in Optical Coherent Flexible Bit-Rate Receivers in the Presence of State-of-Polarization Transients and Colored Noise by Ahmad Abdo, Claude D’Amours

“…However, the three algorithms have similar tracking capabilities in the absence of colored noise.…”
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Predicting Weather Disruptions for the ICC Champions Trophy 2025 in Pakistan Using Machine Learning and Data Analytics by Syeda Faiza Nasim, Umm-e-Kulsoom, Syeda Alishba Fatima, Salka Naushad

“…Our approach comprised combining real-time analytics with historical weather data from Open-Meteo, as well as using Python tools and the Machine Learning algorithm to predict rain during a game. Power BI is used to show the results, giving a thorough understanding of the climatic trends in three important cities: Karachi, Lahore, and Rawalpindi. …”
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Novel methods for selecting stock portfolio in conditions of uncertainty and forecasting with RR-DEA, ANFIS, FGP: A case study of Tehran stock exchange. by Mohammadmahdi Taheri, Amir Azizi, Emran Mohammadi, Abbas Saghaei

“…Portfolio selection and management are two of the most important decisions in the financial field. The existence of uncontrollable factors affects the decision-making process, which is a problem for investors who are responsible for the final financial decisions on how to allocate their budgets to financial assets in their investment portfolios. …”
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CDBR: A semi-automated collaborative execute-before-after dependency-based requirement prioritization approach by Ankita Gupta, Chetna Gupta

“…The presented approach targets three major constraints rarely addressed in existing work, namely dependencies among requirements, communication among stakeholder and developers and the issue of scalability. …”
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A Hybrid MCDM-Grey Wolf Optimizer Approach for Multi-Objective Parametric Optimization of μ-EDM Process by Partha Protim Das

“…This paper attempts to demonstrate the applicability of three well-known multi-criteria decision-making (MCDM) techniques, including the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), multi-attributive border approximation area comparison (MABAC), and complex proportional assessment (COPRAS) methods, separately hybridized with the grey wolf optimization (GWO) algorithm. …”
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An approach to forecast production profiles, oil-gas ratio and water contamination probabilistic assessment by D. V. Balin, O. V. Balina, E. I. Mamchistova

“…The variants of variables implementation were studied, the review of experimental designs and optimiza­tion algorithms was done. At the first step, the simulation model was history matched using Differential Evolution algorithm, since its initial version had problems with phase withdrawals and pressure dynamics. …”
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Research on cultivating students’ creative thinking ability in art design teaching based on machine learning by Ke Xue

“…By analyzing system requirements and employing AI visual elements, the three models: the user, the window, and the display, are utilized to create a robust system hierarchy. …”
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Optimal policy for composite sensing with crowdsourcing by Bei Zhao, Siwen Zheng, Jianhui Zhang

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Online Intelligent Monitoring System and Key Technologies for Dam Operation Safety by Shuangping Li, Bin Zhang, Guangqin Tong, Yonghua Li, Zuqiang Liu, Bo Shi, Jun Geng, Dingming Liu, Huawei Wang, Qingsong Ai, Jianxin Ding, Zheng Gan

“…Leveraging our proprietary innovations, including a GIS + BIM digital base, smart algorithm matrix, and BIM-based finite element computing system, we successfully developed the Three Gorges Dam intelligent monitoring platform, delivering five core value propositions: (1) Achieve real-time and historical aggregation of comprehensive data with dam safety management as the core, fully encompassing various types of environmental monitoring data. (2) Utilizing “GIS + BIM” as the technical foundation, construct a digital twin geometric model of the hub monitoring physical world, enabling intuitive and precise representation of engineering status. (3) Implement online rapid structural calculation, analysis, and early warning based on “BIM + Finite Element” technology, providing timely and reliable support for safety decision-making. (4) Establish a monitoring data analysis model through machine learning intelligent algorithms, deeply mining data value to enable intelligent prediction of potential safety hazards. (5) Promote digital transformation of manual inspection workflows using “IOT + Micro-INS” technology, enhancing inspection efficiency and accuracy. …”
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CUSTOMER BEHAVIOR TRANSFORMATION: HISTORY AND TODAY by N. V. Barinova

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An Efficient Prediction System for Diabetes Disease Based on Deep Neural Network by Tawfik Beghriche, Mohamed Djerioui, Youcef Brik, Bilal Attallah, Samir Brahim Belhaouari

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Risk prediction and effect evaluation of complicated appendicitis based on XGBoost modeling by Sunmeng Chen, Jianfu Xia, Beibei Xu, Yi Huang, Miaomiao Teng, Juyi Pan

“…Methods Patient data from 773 appendectomies were retrospectively collected, important features were selected using random forests, and the data were divided into training and test sets in a 3:1 ratio. An integrated learning algorithm, Extreme Gradient Boosting (XGBoost), was introduced to predict the risk of CAP and compared with Support Vector Machine (SVM), Random Forest (RF), and Decision Tree (CART) algorithms. …”
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