USING MONARCH BUTTERFLY OPTIMIZATION TO SOLVE THE EMERGENCY VEHICLE ROUTING PROBLEM WITH RELIEF MATERIALS IN SUDDEN DISASTERS

Using Monarch Butterfly Optimization to Solve the Emergency Vehicle Routing Problem with Relief Materials in Sudden Disasters

China has one of the highest rates of natural disasters in the world.In recent years, the Chinese government has placed a high value on improving emergency natural disaster relief.The goal of this research was to resolve a key issue for emergency natural disaster relief: the emergency vehicle routing problem (EmVRP) with relief materials in sudden

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Double-Condensing Attention Condenser: Leveraging Attention in Deep Learning to Detect Skin Cancer from Skin Lesion Images

Skin cancer is the most common type Chairs of cancer in the United States and is estimated to affect one in five Americans.Recent advances have demonstrated strong performance on skin cancer detection, as exemplified by state of the art performance in the SIIM-ISIC Melanoma Classification Challenge; however, these solutions leverage ensembles of co

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Leaf Area Index Estimation Algorithm for GF-5 Hyperspectral Data Based on Different Feature Selection and Machine Learning Methods

Leaf area index (LAI) is an essential vegetation parameter that represents the light energy utilization and vegetation canopy structure.As the only in-operation hyperspectral satellite launched by China, GF-5 is potentially useful for accurate LAI estimation.However, there is no research focus on evaluating GF-5 data 24" Wall Oven for LAI estimatio

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