Keywords:
Artificial intelligence.
;
Application software.
;
Algorithms.
;
Electronic books.
Type of Medium:
Online Resource
Pages:
1 online resource (771 pages)
Edition:
1st ed.
ISBN:
9783319320342
Series Statement:
Lecture Notes in Computer Science Series ; v.9648
URL:
https://ebookcentral.proquest.com/lib/geomar/detail.action?docID=6303379
DDC:
006.3
Language:
English
Note:
Intro -- Preface -- Organization -- Contents -- Data Mining and Knowledge Discovery -- Screening a Case Base for Stroke Disease Detection -- Abstract -- 1 Introduction -- 2 Knowledge Representation and Reasoning -- 3 A Case Study -- 4 Case Based Reasoning -- 5 Conclusions -- Acknowledgments -- References -- SemSynX: Flexible Similarity Analysis of XML Data via Semantic and Syntactic Heterogeneity/Homogeneity Detection -- 1 Introduction -- 1.1 On the Innovativeness of the SemSynX Proposal -- 2 Running Example -- 3 The SemSynX Approach -- 3.1 XML Data Similarity Analysis in SemSynX -- 4 Experimental Results -- 5 Conclusions and Future Work -- References -- Towards Automatic Composition of Multicomponent Predictive Systems -- 1 Introduction -- 2 Related Work -- 3 MCPS Description -- 4 Contribution to Auto-WEKA -- 5 Methodology -- 6 Results and Discussion -- 7 Conclusion and Future Work -- References -- LiCord: Language Independent Content Word Finder -- 1 Introduction -- 2 Related Work -- 3 LiCord: Proposed Framework -- 3.1 NGram Constructor -- 3.2 Function Word Decider -- 3.3 Feature Value Calculator -- 3.4 Classifier Learner -- 4 Experiment -- 4.1 Experiment 1 -- 4.2 Experiment 2 -- 5 Conclusion -- References -- Mining Correlated High-Utility Itemsets Using the Bond Measure -- 1 Introduction -- 2 Preliminaries and Related Work -- 3 The FCHM Algorithm -- 4 Experimental Study -- 5 Conclusion -- References -- An HMM-Based Multi-view Co-training Framework for Single-View Text Corpora -- 1 Introduction -- 2 View Generation -- 3 Co-training with HMM View -- 4 Experiments -- 5 Results -- 6 Conclusions -- References -- Does Sentiment Analysis Help in Bayesian Spam Filtering? -- 1 Introduction -- 2 Related Work -- 2.1 Spam Filtering Techniques -- 2.2 Sentiment Analysis -- 3 Improving Spam Filtering Using Sentiment Analysis -- 3.1 Bayesian Spam Filtering.
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3.2 Sentiment Analysis -- 4 Experimental Results -- 4.1 Bayesian Spam Filtering Experiment -- 4.2 Sentiment Analysis -- 5 Conclusions -- References -- A Context-Aware Keyboard Generator for Smartphone Using Random Forest and Rule-Based System -- Abstract -- 1 Introduction -- 2 Related Works -- 3 Adaptive Keyboard Generator -- 3.1 Data Collection -- 3.2 Data Analysis -- 3.3 User Behavior Pattern Recognition -- 3.4 GUI Generation -- 4 Experimental Results -- 5 Concluding Remarks -- Acknowledgements -- References -- Privacy Preserving Data Mining for Deliberative Consultations -- 1 Introduction -- 2 Privacy Preserving Data Mining for Deliberative Consultations - Literature Review -- 2.1 Levels of Privacy Preserving -- 2.2 Types of Data Partitioning in Privacy Preserving Data Mining -- 2.3 Methods of Data Modification in Privacy Preserving Data Mining -- 2.4 Privacy Preserving Techniques -- 3 Usability of Privacy Preserving Techniques in Deliberative Consultations -- 4 Conclusions and Future Work -- References -- Feature Selection Using Approximate Multivariate Markov Blankets -- 1 Introduction -- 2 Theoretical Foundations -- 2.1 Bivariate Approach for Feature Redundancy -- 2.2 Multivariate Approach -- 3 Data -- 3.1 Synthetic Datasets -- 3.2 UCI Datasets -- 4 Experiments and Results -- 4.1 Synthetic Datasets -- 4.2 UCI Datasets -- 5 Conclusions and Future Works -- References -- Student Performance Prediction Applying Missing Data Imputation in Electrical Engineering Studies Degree -- Abstract -- 1 Introduction -- 2 Case of Study -- 3 The Used Data Imputation Techniques -- 3.1 The MICE Algorithm -- 3.2 The AAA Algorithm -- 3.3 Models Validation -- 4 Results -- 5 Conclusions -- Acknowledgments -- References -- Accuracy Increase on Evolving Product Unit Neural Networks via Feature Subset Selection -- 1 Introduction -- 2 Methodology.
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2.1 Product Unit Neural Networks and Training Procedure -- 2.2 Experimental Design Distribution -- 2.3 Feature Selection -- 3 Proposal Description -- 4 Experimentation -- 5 Results -- 5.1 Results Applying EDD and EDDFS -- 5.2 Results Obtained with State-of-the-art Classifiers -- 6 Conclusions -- References -- Time Series -- Rainfall Prediction: A Deep Learning Approach -- 1 Introduction -- 2 Related Work -- 3 Data Preparation -- 4 Proposed Architecture -- 5 Experiments -- 5.1 Optimizing the Proposed Network Architecture -- 5.2 Evaluation of the Proposed Network -- 6 Conclusions and Future Work -- References -- Time Series Representation by a Novel Hybrid Segmentation Algorithm -- 1 Introduction -- 2 Hybrid Segmentation Algorithm -- 2.1 Summary of the Algorithm -- 2.2 Genetic Algorithm -- 2.3 Local Search -- 3 Experimental Results and Discussion -- 3.1 Time Series Analysed -- 3.2 Experimental Setting -- 3.3 Discussion -- 4 Conclusions -- References -- A Nearest Neighbours-Based Algorithm for Big Time Series Data Forecasting -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Time Series Forecasting Based on Nearest Neighbours -- 3.2 Algorithm Implementation for Apache Spark -- 4 Results -- 4.1 Datasets Description -- 4.2 Design of Experiments -- 4.3 Electricity Consumption Big Data Time Series Forecasting -- 5 Conclusions -- References -- Active Learning Classifier for Streaming Data -- 1 Introduction and Related Works -- 2 Active Learning Classifier for Data Stream -- 3 Experiments -- 3.1 Goals -- 3.2 Results -- 3.3 Discussion -- 4 Conclusions -- References -- Bio-inspired Models and Evolutionary Computation -- Application of Genetic Algorithms and Heuristic Techniques for the Identification and Classification of the Information Used by a Recipe Recommender -- 1 Introduction -- 2 Specification of the Proposed Genetic Algorithm.
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2.1 Codification -- 2.2 Starting Generation -- 2.3 GA Operators -- 2.4 Fitness Function -- 2.5 Getting the New Generation -- 2.6 Results -- 3 Heuristics -- 4 Conclusions -- References -- A New Visualization Tool in Many-Objective Optimization Problems -- 1 Introduction -- 2 Related Work -- 3 Proposed Tool -- 3.1 Overview Step -- 3.2 Detail Step -- 4 Experimental Results -- 5 Conclusion -- References -- A Novel Adaptive Genetic Algorithm for Mobility Management in Cellular Networks -- 1 Introduction -- 2 Basic Concepts -- 2.1 The Genetic Algorithm -- 2.2 Adaptation Within Evolutionary Algorithms -- 2.3 Studied Adaptation Strategies -- 2.4 Mobility Management in Cellular Networks -- 3 The Proposed Approach -- 3.1 Initialisation -- 3.2 Selection -- 3.3 Reproduction -- 3.4 Evaluation and Replacement -- 4 Experimental Results and Analysis -- 4.1 Numerical Results -- 4.2 Discussion and Interpretation -- 5 Conclusions -- References -- Bio-Inspired Algorithms and Preferences for Multi-objective Problems -- 1 Introduction -- 2 Foundations -- 3 Interactive Algorithms -- 3.1 CI-NSGA-II -- 3.2 CI-SMS-EMOA -- 3.3 CI-SPEA2 -- 4 Performance Indicators -- 4.1 Referential Cluster Variance Indicator -- 4.2 Hull Volume Indicator -- 5 Experimental Results -- 6 Final Remarks -- References -- Assessment of Multi-Objective Optimization Algorithms for Parametric Identification of a Li-Ion Battery Model -- 1 Introduction -- 2 Semi-physical Model for Li-Ion Battery -- 3 Multi-Objective Approach for Semi-physical Models -- 4 Experimental Results -- 4.1 Experimental Setup and Electronic Instrumentation -- 4.2 Statistical Experimental Design -- 4.3 Numerical Results and Discussion -- 5 Conclusion -- References -- Comparing ACO Approaches in Epilepsy Seizures -- 1 Introduction -- 2 FRBC Learning Metaheuristics for ECI -- 2.1 Pittsburg Learning of Generalized FRBC Models.
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2.2 Ant-Miner+ for Learning FRBCs with Michigan Style -- 3 Experimentation and Results -- 3.1 Materials and Methods -- 3.2 Evaluating the Effect of the Partitioning in the ACO Pittsburg Learning and Ant-Miner+ Michigan Approach -- 4 Conclusions and Future Work -- References -- Estimating the Maximum Power Delivered by Concentrating Photovoltaics Technology Through Atmospheric Conditions Using a Differential Evolution Approach -- 1 Introduction -- 2 CPV Technology -- 2.1 Study of Influential Atmospheric Conditions on the Electric Performance of CPV Modules -- 2.2 The Use of SMR and APE Indexes to Characterise the DNI Spectral Distribution -- 3 Experimental Study -- 4 Conclusions -- References -- A Hybrid Bio-inspired ELECTRE Approach for Decision Making in Purchasing Agricultural Equipment -- Abstract -- 1 Introduction -- 2 Agricultural Decision Making and Related Work -- 3 A Hybrid Bio-Inspired ELECTRE Model -- 3.1 Multiple Criteria Decision Making ELECTRE I Model -- 3.2 Application of Bio-Inspired Ranking Method -- 4 Choosing and Decision Making for Agricultural Equipment -- 4.1 Data Collection - Combine Harvester -- 5 Experimental Results -- 5.1 Experimental Results - Combine Harvester -- 5.2 Complete Ranking PROMETHEE II Method - Experimental Results -- 5.3 Discussion on Experimental Results -- 5.4 Experimental Results - Purchasing Irrigation Equipment -- 6 Conclusion and Future Work -- Acknowledgments -- References -- Learning Algorithms -- Evaluating the Difficulty of Instances of the Travelling Salesman Problem in the Nearby of the Optimal Solution Based on Random Walk Exploration -- 1 Introduction -- 2 Related Work -- 3 Methodology -- 3.1 Travelling Salesman Problem and Instances -- 3.2 Experimental Setup -- 4 Analysis -- 4.1 How Far from the Optimal Fitness? -- 4.2 Area as Metric -- 4.3 Comparison with the Phase Transition Parameter for TSP.
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5 Conclusions and Future Work.
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