Soft Computing and Its Engineering Applications 5th International Conference, icSoftComp 2023, Changa, Anand, India, December 7–9, 2023, Revised Selected Papers, Part II

The two-volume proceedings constitutes the refereed proceedings of the 5th International Conference on Soft Computing and its Engineering Applications, icSoftComp 2023, held in Changa, Anand, India, in December 2023. 

Systems and Applications.- Metagenomic Gene Prediction Using Bidirectional LSTM.- Energy-Efficient Task Scheduling in Fog Environment using TOPSIS.- Dynamic Underload Host Detection for Performance Enhancement in Cloud Environment.- Inverse Reinforcement Learning to Enhance Physical Layer Security in 6G RIS-Assisted Connected Cars.- Computer Vision-Based Cybersecurity Threat Detection System with GAN-Enhanced Data Augmentation.- Classification using Optimal Polarimetric Parameters for Compact Polarimetric Data.- Comparative study of Supervised Classification for LULC Using Geospatial Technology.- A U-Net Based Approach for High-Accuracy Land Use Land Cover Classification in Hyperspectral Remote Sensing.- Novel Channel Fuzzy Logic System Modeling for Aquatic Acoustic Wireless Communication within a Tank.- Iterative Interference Cancellation for STBC-OFDM System over Doubly Selective Channel.- Managing Multiple Identities of IoT Devices Using Blockchain.- Machine Learning Enabled Image Classification Using K-Nearest Neighbour and Learning Vector Quantization.- Enhancing IDC Histopathology Image Classification: A Comparative Study of Fine-tuned and Pretrained Models.- Optimized Path Planning Techniques for Navigational Control of Mobile Robot Using Grass Fire Algorithm in Obstacle Environmental.- A Novel Approach for Suggestions on Law Based Problems.- Performance Evaluation of Service Broker Policies in Cloud Computing Environment using Round Robin.- A Course Study Planning Framework – An Engineering Perspective.- Three Languages Simulate Polygons and Perform on the Web.- Hybrid Techniques.- Multi Disease Prediction using Ensembling of distinct Machine Learning and Deep Learning Classifiers.- Resource Management through Workload Prediction Using Deep Learning in Fog-Cloud Architecture.