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Full Description
This two-volume book presents the outcomes of the 8th International Conference on Soft Computing for Problem Solving, SocProS 2018. This conference was a joint technical collaboration between the Soft Computing Research Society, Liverpool Hope University (UK), and Vellore Institute of Technology (India), and brought together researchers, engineers and practitioners to discuss thought-provoking developments and challenges in order to select potential future directions. The book highlights the latest advances and innovations in the interdisciplinary areas of soft computing, including original research papers on algorithms (artificial immune systems, artificial neural networks, genetic algorithms, genetic programming, and particle swarm optimization) and applications (control systems, data mining and clustering, finance, weather forecasting, game theory, business and forecasting applications). It offers a valuable resource for both young and experienced researchers dealing with complex and intricate real-world problems that are difficult to solve using traditional methods.
Contents
Study of Squeeze Film in a Ferrofluid Lubricated Longitudinally Rough Rotating Plates.- Study of Longitudinal Roughness on Hydromagnetic Squeeze Film Between Conducting Rotating Circular Plates.- Fuzzy Logic Based Packet Dropping Detection Approach for Mobile Ad-hoc Wireless Network.- Optimization of Parking Lot Area in Smart Cities Using Game Theory.- Analysis of Spatial Domain Image Steganography Based on Pixel Value Differencing Method.- Passive Bandwidth Estimation Techniques for QoS Routing in Wireless LANs.- Toward Automatic Scheduling Algorithm With Hash-based Priority Selection Strategy.- Agent-Based Modeling of the Adaptive Immune System Using Netlogo Simulation Tool.- Object Classification from Shape Detection.- Analysis of Road Networks Using the Louvian Community Detection Algorithm.- Congestion Control Using Fuzzy Based Node Reliabilityand Rate Control.- Impact of Inertia Weight and Cognitive and Social Constants in Obtaining Best Mean Fitness Value for PSO.
