UID:
almahu_9948029452702882
Format:
XVII, 991 p. 397 illus., 240 illus. in color.
,
online resource.
ISBN:
9789811315954
Series Statement:
Advances in Intelligent Systems and Computing, 817
Content:
This two-volume book presents outcomes of the 7th International Conference on Soft Computing for Problem Solving, SocProS 2017. This conference is a joint technical collaboration between the Soft Computing Research Society, Liverpool Hope University (UK), the Indian Institute of Technology Roorkee, the South Asian University New Delhi and the National Institute of Technology Silchar, and brings together researchers, engineers and practitioners to discuss thought-provoking developments and challenges in order to select potential future directions The book presents the latest advances and innovations in the interdisciplinary areas of soft computing, including original research papers in the areas including, but not limited to, 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 is a valuable resource for both young and experienced researchers dealing with complex and intricate real-world problems for which finding a solution by traditional methods is a difficult task.
Note:
A Multiscale Retinex with Colour Restoration (MSR-CR) Technique For Skin Cancer Detection -- Efficient License Plate Recognition System with Smarter Interpretation Through IoT -- Image Captioning Based Image Search Engine: An Alternative to Retrieval by Metadata -- Demand Side Management of a Commercial Customer Based on ABC Algorithm -- Trapezoidal Intuitionistic Fuzzy Fractional Transportation Problem -- How Delay Can Affect the Survival of Species in Polluted Environment -- Local Invariant Features Based Gender Recognition from Facial Images -- Enhancing Saliency of a Target Object Through Color Modification of Every Object Using Genetic Algorithm.
In:
Springer eBooks
Additional Edition:
Printed edition: ISBN 9789811315947
Additional Edition:
Printed edition: ISBN 9789811315961
Language:
English
DOI:
10.1007/978-981-13-1595-4
URL:
https://doi.org/10.1007/978-981-13-1595-4
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