Titlebook: Soft Computing and Its Engineering Applications; 5th International Co Kanubhai K. Patel,KC Santosh,Ashish Ghosh Conference proceedings 2024

事物的方面

Dynamic Underload Host Detection for Performance Enhancement in Cloud Environmentf linear regression method. Our proposed approach aims to simultaneously reduce consumption of energy, minimize virtual machine (VM) migration and uphold SLA (Service Level Agreement) compliance. Any reduction in the number of VM migrations, results in better resource utilization and also mitigates

INTER

Inverse Reinforcement Learning to Enhance Physical Layer Security in 6G RIS-Assisted Connected Carsavesdropper’s attempts and bolstering communication security. Secondly, the extensive derivations of performance metrics - signal-to-interference noise ratio and bit error rate have been carried out to show the importance of IRL approach. Through comprehensive simulations, the efficacy of the propos

Radiculopathy

Incorruptible

Comparative Study of Supervised Classification for LULC Using Geospatial Technology, Fallow Land and Built-up areas; due to their spectral signature similarity. The Landsat 8 image were captured on 6 May 2022, and this is a post harvesting period, so naturally there should be more Fallow land which is identified by SAM Classifier. Minimum Distance classifier identify 1.15% land as

evince

碎石

Novel Channel Fuzzy Logic System Modeling for Aquatic Acoustic Wireless Communication Within a Tanknts, and coverage area for acoustic signals in the underwater frequency range. Fuzzy logic analysis provides comprehensive insights into underwater communication dynamics, specifically assessing the attenuation of acoustic frequency signals.

somnambulism

陶器

Machine Learning Enabled Image Classification Using K-Nearest Neighbour and Learning Vector Quantizatting, and the implementation followed specifically due to the metrics result with 96.67% accuracy, 1.00 precision, 0.89 recall, and 0.94 F1 Score. Hence, KNN can be applied for effective image classification problems. KNN and LVQ both have their strength and weaknesses depending on the problem at h

Efflorescent

reperfusion

Performance Evaluation of Service Broker Policies in Cloud Computing Environment Using Round Robins). The experimental results convey that the SBPs CDC, OptiResTime, and RD take an average OvrallResTime of 1310.68 ms, 1310.92 ms, and 8226.72 ms, respectively. Concerning DCPT, the SBPs CDC, OptiResTime, and RD take an average of 1010.71 ms, 1010.66 ms, and 7925.28 ms, respectively. Hence, the SBP