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Titlebook: Intelligent Computing Paradigm: Recent Trends; J. K. Mandal,Devadutta Sinha Book 2020 Springer Nature Singapore Pte Ltd. 2020 Intelligent

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楼主: Magnanimous
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Improved Hybrid Approach of Filtering Using Classified Library Resources in Recommender System, update user profiles and search the proper library resources. This proposed system uses a hybrid approach for filtering available books of different subjects, research journal articles, and other resources. Content-based filtering evaluates user profile with available library resources. The results
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Artificial Intelligent Reliable Doctor (AIRDr.): Prospect of Disease Prediction Using Reliability,nd sometimes although doctors are available but people are not able to afford them due to financial issues. The basic information like blood pressure, ages, etc. are known at that moment without knowing any symptoms how the disease can be predicted. If people know the symptoms of how the disease can
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Forest Cover Change Analysis in Sundarban Delta Using Remote Sensing Data and GIS,ed maximum likelihood classification techniques are needed to classify the remote sensing data, and the classes are water body, barren land, dense forest, and open forest. The study reveals that forest cover areas have been increased by 1.06% (19.28 km.), 5.80% (106.82 km.) during the periods of 197
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Identification of Malignancy from Cytological Images Based on Superpixel and Convolutional Neural Nimages to eradicate human intervention, this chapter draws curtain from the history of automated CAD-based design system for better understanding of the roots of the evolving image processing techniques in the analysis of biomedical images. Our first approach introduces the clustering-based approach
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Book 2020ce City, Kolkata on 19–21 January 2018. It features a collection of chapters focusing on recent trends in computational intelligence, covering topics such as ANN, neuro-fuzzy based clustering, edge detection, data mining, mobile cloud computing, intelligent scheduling, processing and authentication.
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Bacterial Foraging Optimization-Based Clustering in Wireless Sensor Network by Preventing Left-Out is paper as an optimization method for improving the clustering performance in WSN by preventing left-out node’s formation. The performance of BFAO is compared with the Particle Swarm Optimization (PSO) and LEACH. The results show that the BFAO performance is better than PSO and LEACH in improving the lifetime of network and throughput.
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