AI-Driven Drought Monitoring: Advanced Machine Learning Techniques for Early Prediction by Vij Priya, Tiwari Ankita

“…Moreover, the research conducts a comparative evaluation of various machine learning models to identify the most effective algorithms for different climatic zones and crop types. …”
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The Synergy of Minds and Machines: Rethinking the AI-HI Relationship through Dialectical Reconstruction by Ridwan Ishola MOGAJI, Adewale Oluwaseun MOTADEGBE

“…Artificial intelligence on the other hand is the simulation of human cognitive functions by machines, especially in tasks such as problem-solving, pattern recognition, and decision-making, which often operates based on algorithms and data, both of which are unique and important in themselves. …”
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Machine learning–based feature prediction of convergence zones in ocean front environments by Weishuai Xu, Lei Zhang, Hua Wang

“…The convergence zone holds significant importance in deep-sea underwater acoustic propagation, playing a pivotal role in remote underwater acoustic detection and communication. Despite the adaptability and predictive power of machine learning, its practical application in predicting the convergence zone remains largely unexplored. …”
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Smart grid stability prediction using Adaptive Aquila Optimizer and ensemble stacked BiLSTM by Safwan Mahmood Al-Selwi, Mohd Fadzil Hassan, Said Jadid Abdulkadir, Mohammed Gamal Ragab, Alawi Alqushaibi, Ebrahim Hamid Sumiea

“…Methods: This study introduces an ensemble stacked bidirectional Long Short-Term Memory model enhanced by a proposed Adaptive Aquila Optimizer (AAO). The AAO uses a Sigmoid Factor to balance exploration and exploitation, adapting the transition from broad searches to focused ones based on iteration progress. …”
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From Mountains to Basins: Asymmetric Ecosystem Vulnerability and Adaptation to Extreme Climate Events in Southwestern China by Qingao Lu, Yuandong Zhang, Wei Sun, Jingxuan Wei, Kun Xu

“…The increasing frequency of both singular and compound extreme climate events driven by global warming has profoundly impacted terrestrial ecosystems. Using machine learning-based Random Forest algorithms and moving correlation analysis, this study quantifies the impacts of extreme climate indices (ECIs) on two ecological indicators (EIs), the NDVI and GPP, from 1982 to 2019. …”
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RU-OLD: A Comprehensive Analysis of Offensive Language Detection in Roman Urdu Using Hybrid Machine Learning, Deep Learning, and Transformer Models by Muhammad Zain, Nisar Hussain, Amna Qasim, Gull Mehak, Fiaz Ahmad, Grigori Sidorov, Alexander Gelbukh

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Optimization and Trends in EV Charging Infrastructure: A PCA-Based Systematic Review by Javier Alexander Guerrero-Silva, Jorge Ivan Romero-Gelvez, Andrés Julián Aristizábal, Sebastian Zapata

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Application of Levy flight-based harmony search algorithm for the flexible job shop scheduling by Jun Li, Yang Zhou

“…To this end, this study proposed a Levy flight-based Harmony Search algorithm (LHS), which effectively avoids premature convergence by dynamically and adaptively adjusting the Harmony Memory Considering Rate (HMCR), the probability of Pitch Adjusting Rate (PAR), and the arbitrary distance Bandwidth(BW), and by introducing a Levy flight mechanism to perturb the parameters to broaden the search space and enhance the diversity of the population. …”
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Decoding development: the AI frontier in policy crafting: A systematic review by Sofiarti Dyah Anggunia, Jesse Sowell, María Pérez-Ortiz

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Urban flood hazard assessment using FLA-optimized boost algorithms in Ankara, Türkiye by Enes Gul

“…The implications of this research extend beyond the local setting, contributing valuable insights to the global discourse on climate change adaptation and urban resilience. By combining cutting-edge machine learning techniques with in-depth geographic analysis, this study offers a scalable and innovative model for flood hazard assessment and management, providing a critical tool for cities around the world facing similar challenges.…”
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Revisiting Online Algorithms: A Survey of Set Cover Solutions Beyond Competitive Analysis by Christine Markarian, Claude Fachkha, Noura Yassine

“…Online algorithms are crucial for real-time decision-making and adaptability across diverse fields, such as operations research, computer science, and combinatorics. …”
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An Explainable LSTM-Based Intrusion Detection System Optimized by Firefly Algorithm for IoT Networks by Taiwo Blessing Ogunseyi, Gogulakrishan Thiyagarajan

“…The performance of the proposed model is compared with that of other machine learning models and existing state-of-the-art models, demonstrating superior accuracy. …”
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Management and prediction of river flood utilizing optimization approach of artificial intelligence evolutionary algorithms by Rana Muhammad Adnan Ikram, Mo Wang, Hossein Moayedi, Atefeh Ahmadi Dehrashid

“…This study evaluates the performance of artificial neural network (ANN) algorithms for FSM using machine learning classification. …”
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Modeling saturation exponent of underground hydrocarbon reservoirs using robust machine learning methods by Abhinav Kumar, Paul Rodrigues, A. K. Kareem, Tingneyuc Sekac, Sherzod Abdullaev, Jasgurpreet Singh Chohan, R. Manjunatha, Kumar Rethik, Shivakrishna Dasi, Mahmood Kiani

“…In this communication, we aim to develop intelligent data-driven models of decision tree, random forest, ensemble learning, adaptive boosting, support vector machine and multilayer perceptron artificial neural network to predict rock saturation exponent parameter in terms of rock absolute permeability, porosity, resistivity index, true resistivity, and water saturation based on acquired 1041 field data. …”
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An improved Red-billed blue magpie feature selection algorithm for medical data processing. by Chenyi Zhu, Zhiyi Wang, Yinan Peng, Wenjun Xiao

“…The core mechanisms of IRBMO include: elite search behavior, which improves global optimization by guiding the search to expand in more promising directions; collaborative hunting behavior, which quickly identifies key features and promotes collaborative optimization among feature subsets; and memory storage behavior, which leverages historically valid information to improve search efficiency and accuracy. To adapt to the feature selection problem, we convert the continuous optimization algorithm to binary form via transfer function, which further enhances the applicability of the algorithm. …”
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Territorial Space Optimization Method Based on Multi-Objective Genetic Algorithm and FLUS Model by Lin Ge

“…For additional spatial layout design, the study suggests a multi-objective genetic algorithm based on spatial data prediction and coupled with land simulation modeling in the context of big data and machine learning development. …”
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Type-3 Fuzzy Dynamic Adaptation of the Crossover Parameter in Differential Evolution for the Optimal Design of Type-3 Fuzzy Controllers for the Inverted Pendulum by Patricia Ochoa, Cinthia Peraza, Patricia Melin, Oscar Castillo, Zong Woo Geem

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Prediction of Moisture Content in Kiwi (Actinidia deliciosa) Dried Using Machine Learning Approaches by Halil Nusret BULUS, Soner CELEN

“…The aim of this research is to compare prediction models developed using two popular machine learning approaches in recent years: Adaptive Neuro-Fuzzy Inference Systems (ANFIS) and Artificial Neural Networks (ANN). …”
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Research on bearing fault feature transfer diagnosis based on balanced distribution adaptation under feature fusion by Lulu Wang, Yongqi Li, Chunyi Zhang, Ralph Gerard Sangalang

“…To address this issue, this paper proposes a bearing fault transfer diagnosis method that combines the Balanced Distribution Adaptation (BDA) algorithm with a Back Propagation neural network (BPNN) classification algorithm. …”
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Leveraging the Power of Deep Learning Technique for Creating an Intelligent, Context-Aware, and Adaptive M-Learning Model by Muhammad Adnan, Duaa H. AlSaeed, Heyam H. Al-Baity, Abdur Rehman

“…Machine learning (ML) and deep learning (DL) algorithms work well where future estimations and predictions are required. …”
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