Buch, Englisch, 140 Seiten, Format (B × H): 155 mm x 235 mm
Volume 23
Buch, Englisch, 140 Seiten, Format (B × H): 155 mm x 235 mm
Reihe: Studies in Computational Intelligence
ISBN: 978-3-032-18569-3
Verlag: Springer
This book reports state-of-the art results in Software Engineering, Artificial Intelligence, Networking and Parallel/Distributed Computing in both printed and electronic form. Studies in Computation Intelligence (SCI) has grown into the most comprehensive computational intelligence research forum available in the world.
This book published original papers on both theory and practice that address foundations, state-of-the art problems and solutions, and crucial challenges.
Zielgruppe
Research
Autoren/Hrsg.
Fachgebiete
Weitere Infos & Material
Design and Evaluation of a Lightweight Encryption Architecture Based on LEA-CBD.- Irrigation Scheduling for Tomato Cultivation Using ROCKET-Based Time Series Analysis.- Utilizing PID Control to Balance Temperature and performance analysis.- Research on multimodal data fusion for crop disease prediction.- Designing an automated control algorithm to regulate CO2 concentration in greenhouses using XGBoost.- Smart Farm Environment Control System Based on Safety Reinforcement Learning.- Growing Vertical Farm Leafy Greens with LED Spec-trum Analysis by Growth Stage and Energy Efficiency Optimization Research.- Design of a Hybrid Heating System Utilizing Low-Tem-perature Waste Heat Recovery for Energy Saving in Greenhouse Facilities.- Design and Implementation of a GPT-4o-Based Agricul-tural Chatbot System with Multi-API Integration for Fu-ture Smart Farm Integration.- A Study on the Development of a Classification Code-Based Processing System for Smart Farm Horticultural Waste.- Design of a Smart Home Aquaponics System and Correlation Analysis of Growth Factor.- DETR-Based Object Detection for Pest and Disease Recognition in Agricultural.- Development of Auto-Completion and Correction Tools for Kazakh Language using Natural Language Processing.- Evaluating BiLSTM and CNN+GRU Approaches for Human Activity Recognition Using WiFi CSI Data.
