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Mapping sugarcane plantations in Northeast Thailand using multi-temporal data from multi-sensors and machine-learning algorithms
Published 2025-04-01“…In the second step, the discretization of sugarcane from non-sugarcane classes in the agricultural category was conducted using four efficient machine learning algorithms (decision tree (DT), random forest (RF), support vector machine (SVM), and one-class SVM). …”
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Impact of agricultural industry transformation based on deep learning model evaluation and metaheuristic algorithms under dual carbon strategy
Published 2025-07-01“…In conclusion, the model offers a robust, high-accuracy decision-support tool for promoting low-carbon agricultural development. …”
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Collaborative Search Algorithm for Multi-UAVs Under Interference Conditions: A Multi-Agent Deep Reinforcement Learning Approach
Published 2025-06-01“…Due to the NP-hard nature of this problem, we decompose it into two interconnected Markov decision processes (MDPs): a spectrum collaboration subproblem solved using a received signal strength indicator (RSSI)-aware multi-agent proximal policy optimization (MAPPO) algorithm and a search collaboration subproblem addressed through a target probability map (TPM)-guided MAPPO approach with an innovative action-masking mechanism. …”
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Risk Assessment and Spatial Zoning of Rainstorm and Flood Hazards in Mountainous Cities Using the Random Forest Algorithm and the SCS Model
Published 2025-02-01“…China has a vast land area, with mountains accounting for 1/3 of the country’s land area. Flooding in these areas can cause significant damage to human life and property. …”
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IMPLEMENTATION OF MAPPING-BASED MACHINE LEARNING ALGORITHM AS NON-STRUCTURAL DISASTER MITIGATION TO DETECT LANDSLIDE SUSCEPTIBILITY IN TAKARI DISTRICT
Published 2024-05-01“…A range of machine learning algorithms, including Support Vector Machine, Naive Bayes Classifier, Ordinal Logistic Regression, Random Forest, and Decision Tree, were harnessed to evaluate rainfall data within the context of landslide susceptibility. …”
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Inverse design of high-strength medium-Mn steel using a machine learning-aided genetic algorithm approach
Published 2024-11-01Get full text
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Integrating artificial neural networks, multi-objective metaheuristic optimization, and multi-criteria decision-making for improving MXene-based ionanofluids applicable in PV/T sol...
Published 2024-11-01“…The obtained models are integrated into the multi-objective particle swarm optimization (MOPSO) and multi-objective thermal exchange optimization (MOTEO) algorithms, forming a three-objective optimization problem. …”
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