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|a 9783319979823
|9 978-3-319-97982-3
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|a 10.1007/978-3-319-97982-3
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|a Advances in Computational Intelligence Systems
|h [electronic resource] :
|b Contributions Presented at the 18th UK Workshop on Computational Intelligence, September 5-7, 2018, Nottingham, UK /
|c edited by Ahmad Lotfi, Hamid Bouchachia, Alexander Gegov, Caroline Langensiepen, Martin McGinnity.
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|a 1st ed. 2019.
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|a Cham :
|b Springer International Publishing :
|b Imprint: Springer,
|c 2019.
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|a XII, 394 p. 140 illus.
|b online resource.
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|a text
|b txt
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|a computer
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|a online resource
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|a Advances in Intelligent Systems and Computing,
|x 2194-5357 ;
|v 840
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|a On the Integrity of Performance Comparison for Evolutionary Multi-objective Optimisation Algorithms -- The Influence of Age Assignments on the Performance of Immune Algorithms -- Evolutionary Constraint in Artificial Gene Regulatory Networks -- Exploiting Tournament Selection for Efficient Parallel Genetic Programming -- Solving Partial Differential Equations with Bernstein Neural Networks -- Daily Energy Price Forecasting Using a Polynomial NARMAX Model -- Model Selection in Time Series Forecasting -- Fuzzy Modeling for Uncertain Nonlinear Systems using Fuzzy Equations and Z-numbers -- Medical Expert Systems - A Study of Trust and Acceptance by Healthcare Stakeholders -- Agent Based Micro-Simulation of a Passenger Rail System Using Customer Survey Data -- Fintech Bitcoin Smart Investment based on the Random Neural Network with a Genetic Algorithm -- Generating ANFISs through Rule Interpolation: An Initial Investigation -- Disentangling the Latent Space of (Variational) Autoencoders for NLP -- A Low Computational Approach for Assistive Esophageal Adenocarcinoma and Colorectal Cancer Detection -- Learning from Interaction: An Intelligent Networked based Human-bot and Bot-bot Chatbot System -- A Study on CNN Transfer Learning for Image Classification -- Dendritic Cell Algorithm with Fuzzy Inference System for Input Signal Generation -- A Method of Abstractness Ratings for Chinese Concepts -- Effective Diagnosis of Diabetes with a Decision Tree-initialised Neuro-fuzzy Approach -- A Comparison of Re-sampling Techniques for Pattern Classification in Imbalanced Data-Sets -- Classification of Heterogeneous Data Based on Data Type Impact on Similarity -- Clustering-based Fuzzy Finite State Machine for Human Activity Recognition -- Deep Online Hierarchical Unsupervised Learning for Pattern Mining from Utility Usage Data -- Online Object Trajectory Classification using FPGA-SoC Devices -- Key Frame Extraction and Classification of Human Activities using Motion Energy -- A Comprehensive Obstacle Avoidance System of Mobile Robots Using an Adaptive Threshold Clustering and the Morphin Algorithm -- Physarum Inspired Connectivity and Restoration for Wireless Sensor and Actor Networks -- Mining Unit Feedback to Explore Students' Learning Experiences -- Dimension Reduction Based on Geometric Reasoning for Reducts -- Anomaly Detection in Activities of Daily Living using One-Class Support Vector Machine -- Towards Active Muscle Pattern Analysis for Dynamic Hand Motions via SEMG -- A Novel Crossings-based Segmentation Approach for Gesture Recognition.
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|a This book presents the latest trends in and approaches to computational intelligence research and its application to intelligent systems. It covers a long list of interconnected research areas, such as fuzzy systems, neural networks, evolutionary computation, clustering and classification, machine learning, data mining, cognition and robotics, and deep learning. The individual chapters are based on peer-reviewed contributions presented at the 18th Annual UK Workshop on Computational Intelligence (UKCI-2018), held in Nottingham, UK on September 5-7, 2018. The book puts a special emphasis on novel methods and reports on their use in a wide range of applications areas, thus providing both academics and professionals with a comprehensive and timely overview of new trends in computational intelligence.
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650 |
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|a Computational intelligence.
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650 |
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|a Artificial intelligence.
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650 |
1 |
4 |
|a Computational Intelligence.
|0 http://scigraph.springernature.com/things/product-market-codes/T11014
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650 |
2 |
4 |
|a Artificial Intelligence.
|0 http://scigraph.springernature.com/things/product-market-codes/I21000
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700 |
1 |
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|a Lotfi, Ahmad.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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700 |
1 |
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|a Bouchachia, Hamid.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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700 |
1 |
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|a Gegov, Alexander.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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700 |
1 |
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|a Langensiepen, Caroline.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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700 |
1 |
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|a McGinnity, Martin.
|e editor.
|4 edt
|4 http://id.loc.gov/vocabulary/relators/edt
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710 |
2 |
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|a SpringerLink (Online service)
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773 |
0 |
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|t Springer eBooks
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776 |
0 |
8 |
|i Printed edition:
|z 9783319979816
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776 |
0 |
8 |
|i Printed edition:
|z 9783319979830
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830 |
|
0 |
|a Advances in Intelligent Systems and Computing,
|x 2194-5357 ;
|v 840
|
856 |
4 |
0 |
|u https://doi.org/10.1007/978-3-319-97982-3
|z Full Text via HEAL-Link
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912 |
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|a ZDB-2-INR
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950 |
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|a Intelligent Technologies and Robotics (Springer-42732)
|