Keywords:
Artificial intelligence.
;
Electronic books.
Type of Medium:
Online Resource
Pages:
1 online resource (678 pages)
Edition:
1st ed.
ISBN:
9783030862718
Series Statement:
Lecture Notes in Computer Science Series ; v.12886
URL:
https://ebookcentral.proquest.com/lib/geomar/detail.action?docID=6727156
DDC:
006.3
Language:
English
Note:
Intro -- Preface -- Organization -- Contents -- Data Mining, Knowledge Discovery and Big Data -- Document Similarity by Word Clustering with Semantic Distance -- 1 Introduction -- 2 Vector Space Model and Dimension Reduction -- 2.1 Vector Space Model -- 2.2 Distance by WordNet -- 2.3 Distance by Word2Vec -- 2.4 Word Clustering -- 2.5 Dimension Reduction by Semantic Distance -- 2.6 Cluster-Word Relation Matrix -- 3 Experimental Results -- 3.1 Conditions of Experiments -- 3.2 Similarity of Documents -- 3.3 Result of Each Method -- 4 BBC Dataset -- 5 Conclusion -- References -- PSO-PARSIMONY: A New Methodology for Searching for Accurate and Parsimonious Models with Particle Swarm Optimization. Application for Predicting the Force-Displacement Curve in T-stub Steel Connections -- 1 Introduction -- 2 Related Works -- 3 PSO-PARSIMONY Methodology -- 4 Case Study -- 5 Experiment and Results Discussion -- 6 Conclusions -- References -- Content-Based Authorship Identification for Short Texts in Social Media Networks -- 1 Introduction -- 2 Proposed Approach -- 3 Experiment -- 3.1 Data Gathering -- 3.2 Data Pre-processing -- 3.3 Word Embeddings -- 3.4 Tweet Mean Vectors and User Mean Vectors -- 3.5 Supervised Learning -- 4 Discussion -- 5 Conclusions -- References -- A Novel Pre-processing Method for Enhancing Classification Over Sensor Data Streams Using Subspace Probability Detection -- 1 Introduction -- 2 Related Work -- 3 Our Proposed Model -- 4 Experiment -- 5 Conclusions -- References -- Bio-inspired Models and Evolutionary Computation -- Remaining Useful Life Estimation Using a Recurrent Variational Autoencoder -- 1 Introduction -- 2 RUL Estimation -- 3 Model Architecture -- 4 Experimental Study -- 4.1 Data Pre-processing -- 4.2 Illustrative Example -- 4.3 Numerical Results -- 5 Concluding Remarks -- References.
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Open-Ended Learning of Reactive Knowledge in Cognitive Robotics Based on Neuroevolution -- 1 Introduction -- 2 Knowledge in the Epistemic Multilevel Darwinist Brain (e-MDB) -- 2.1 Knowledge Representation -- 2.2 Knowledge Acquisition and Decision Making -- 3 Policy Learning Process -- 4 Real Robot Example -- 5 Conclusions -- References -- Managing Gene Expression in Evolutionary Algorithms with Gene Regulatory Networks -- 1 Introduction -- 2 Biological Gene Expression -- 3 Gene Regulatory Networks -- 4 Proposed Algorithms -- 4.1 Chromosome Representation -- 4.2 Fitness Evaluation -- 4.3 Mutation -- 4.4 Crossover -- 5 Evaluation -- 6 Results -- 7 Conclusion -- 8 Future Work -- References -- Evolutionary Optimization of Neuro-Symbolic Integration for Phishing URL Detection -- 1 Introduction -- 2 Related Works -- 3 The Proposed Method -- 3.1 Collect and Structuralize Calibration Rules for Deep Learning Classifier -- 3.2 Deep Learning Calibration and Optimization to Improve URL Classification Performance -- 3.3 One-Dimensional Convolutional Recurrent Neural Network to Extract Sequence of Character and Word Features -- 4 Experimental Results -- 4.1 Data Collection -- 4.2 Comparison of Accuracy and Recall Performance -- 4.3 Classification Performance and Chi-Square Test -- 4.4 Analysis of Optimized Combination and Misclassified Cases -- 4.5 Generations for Genetic Algorithm -- 5 Conclusion -- References -- Interurban Electric Vehicle Charging Stations Through Genetic Algorithms -- 1 Introduction -- 2 Problem Description -- 3 Interurban EV Charging Stations Distribution -- 3.1 Utility -- 3.2 Uncovered Area and Distance to Nearest Station -- 3.3 Implementation and Fitness -- 4 Experimental Results -- 5 Conclusions -- References -- An Effective Hybrid Genetic Algorithm for Solving the Generalized Traveling Salesman Problem -- 1 Introduction.
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2 Definition of the Generalized Traveling Salesman Problem -- 3 The Proposed Hybrid Algorithm -- 3.1 Chromosome Structure -- 3.2 Chromosome Optimization -- 3.3 Initial Population -- 3.4 Crossover -- 3.5 Mutation -- 3.6 Genetic Parameters -- 4 Preliminary Computational Results -- 5 Conclusions -- References -- A Simple Genetic Algorithm for the Critical Node Detection Problem -- 1 Introduction -- 2 Related Work -- 3 Maximum Components GA (MaxC-GA) -- 4 Numerical Experiments -- 5 Conclusions -- References -- Learning Algorithms -- Window Size Optimization for Gaussian Processes in Large Time Series Forecasting -- 1 Introduction -- 2 Methodology -- 2.1 Gaussian Processes -- 2.2 Kernel Selection -- 2.3 General Approach to Large Time Series -- 2.4 Data Set -- 3 Results and Analysis -- 3.1 Kernel and Parameter Choice -- 3.2 Hyperparameter Tuning and Interpretability -- 4 Conclusions -- References -- A Binary Classification Model for Toxicity Prediction in Drug Design -- 1 Introduction -- 2 Data and Methods -- 2.1 Dataset Creation -- 2.2 Data Processing -- 2.3 Proposed Model Architecture -- 3 Experiments and Results -- 3.1 Metrics -- 3.2 Scenarios -- 3.3 Results -- 4 Conclusions -- References -- Structure Learning of High-Order Dynamic Bayesian Networks via Particle Swarm Optimization with Order Invariant Encoding -- 1 Introduction -- 2 Background -- 2.1 High-Order Dynamic Bayesian Networks -- 2.2 Particle Swarm Structure Learning -- 3 Encoding and Operators -- 3.1 Natural Vector Encoding -- 3.2 Position and Velocity Operators -- 4 Results -- 4.1 Implementation -- 4.2 Experimental Comparison -- 5 Conclusions -- References -- Prototype Generation for Multi-label Nearest Neighbours Classification -- 1 Introduction -- 2 Related Work -- 3 The Reduction Through Homogeneous Clustering (RHC) Algorithm -- 4 The Proposed Multi-label RHC (MRHC) Algorithm.
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5 Performance Evaluation -- 5.1 Datasets -- 5.2 Experimental Setup -- 5.3 Experimental Results -- 6 Conclusions and Future Work -- References -- Learning Bipedal Walking Through Morphological Development -- 1 Introduction -- 2 Designing a Morphological Development Strategy -- 3 Experimental Setup -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- Ethical Challenges from Artificial Intelligence to Legal Practice -- 1 Introduction. From Justice to eJustice -- 2 Objectives -- 3 Methodology -- 4 Developing. The Application of Algorithms in Justice -- 4.1 Artificial Legal Intelligence -- 4.2 Jurimetrics. Legal Decision Support System -- 4.3 Legal Expert Systems -- 5 Results: First Ethical Questions Derived from the Use of AI in Legal Procedures and Processes -- 5.1 Publicity Principle -- 5.2 Principle of Contradiction and Right of Defense -- 5.3 Principle of Procedural Equality or Equality of the Parts -- 5.4 Influence of AI on the Principles of Criminal Process -- 5.5 Preventive and Predictive AI -- 6 Discussion. Future Challenges: Understandability, Intepretability, Explicability, Transparency, and Algorithmic Traceability as Ethical Challenges -- 6.1 A Relationship Between the Jurimetrics with the Global Framework of the eJustice that Guarantees the Nature of the Latter as an Effective Attorney of Justice -- 6.2 Respect for Procedural Data by Means of Big Data Techniques that Respect the Rights that Are Set Out in Spanish or European Legislation -- 6.3 Transparency in a Digitized Jurisdictional Framework -- 6.4 Establishment of Responsibilities for the People Who Define the Prediction Algorithms on the Prosperousness of a Claim -- 6.5 Irreplaceability of Lawyers or Other Judicial Agents by AI Legal Systems.
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6.6 Guarantee that the Digitization of the Judicial Process Does not Destroy the Analysis and Legal Argumentation that Any Matter Requires -- 7 Conclusions -- 7.1 Need for Codes of Ethics and Legal Regulations Regarding the Use of AI Technologies -- 7.2 Protection of Privacy -- 7.3 Algorithmic Ethics and Research in Explanatory AI (XAI) -- References -- Visual Analysis and Advanced Data Processing Techniques -- Classification of Burrs Using Contour Features of Image in Milling Workpieces -- 1 Introduction -- 2 Inspection Method -- 2.1 Image Processing -- 2.2 Region of Interest Identification -- 2.3 Feature Vector Calculation -- 2.4 Classification -- 3 Experimental Results -- 4 Conclusions -- References -- Adaptive Graph Laplacian for Convex Multi-Task Learning SVM -- 1 Introduction -- 2 Multi-Task Learning SVMs -- 2.1 Convex Multi-Task Learning SVM -- 2.2 Convex Graph Laplacian MTL SVM -- 3 Convex Adaptative Graph Laplacian MTL SVM -- 4 Synthetic Experimental Results -- 5 Discussion and Conclusions -- References -- Fight Detection in Images Using Postural Analysis -- 1 Introduction -- 2 Related Work -- 3 Existing Datasets for Fighting Detection -- 4 Methodology -- 4.1 Data Gathering -- 4.2 Angles Extraction from Skeleton -- 4.3 Dataset Generation -- 5 Experimentation and Results -- 5.1 Feature Subset Selection -- 5.2 Analysis of Network Learning Curves -- 6 Conclusions -- References -- Applying Vector Symbolic Architecture and Semiotic Approach to Visual Dialog -- 1 Introduction -- 2 Related Works -- 3 Vector Semiotic Architecture for Visual Dialog -- 4 Experiments -- 5 Discussion -- 6 Conclusion -- References -- Transfer Learning Study for Horses Breeds Images Datasets Using Pre-trained ResNet Networks -- 1 Introduction and Motivation -- 2 The Proposal -- 3 Numerical Results -- 3.1 Materials and Methods -- 3.2 Results -- 4 Conclusion and Future Work.
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References.
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