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Intelligent Systems

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Cover of 'Intelligent Systems'

Table of Contents

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    Book Overview
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    Chapter 1 A Multi-level Approach to the Formal Semantics of Agent Societies
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    Chapter 2 A Reinforcement Learning Based Adaptive Mutation for Cartesian Genetic Programming Applied to the Design of Combinational Logic Circuits
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    Chapter 3 AgentDevLaw: A Middleware Architecture for Integrating Legal Ontologies and Multi-agent Systems
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    Chapter 4 An Argumentation-Based Approach for Explaining Goals Selection in Intelligent Agents
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    Chapter 5 Application-Level Load Balancing for Reactive Wireless Sensor Networks: An Approach Based on Constraint Optimization Problems
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    Chapter 6 Cooperative Observation of Smart Target Agents
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    Chapter 8 On the Performance of Planning Through Backpropagation
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    Chapter 9 Risk Sensitive Stochastic Shortest Path and LogSumExp: From Theory to Practice
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    Chapter 10 Solving Multi-Agent Pickup and Delivery Problems Using a Genetic Algorithm
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    Chapter 11 Testing Multiagent Systems Under Organizational Model $$\mathcal {M}$$oise Using a Test Adequacy Criterion Based on State Transition Path
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    Chapter 12 A Fuzzy Approach for Classification and Novelty Detection in Data Streams Under Intermediate Latency
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    Chapter 13 A Fuzzy Reasoning Method Based on Ensembles of Generalizations of the Choquet Integral
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    Chapter 14 A Useful Tool to Support the Ontology Alignment Repair
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    Chapter 15 Aggregation with Weak, Axiological and Strong Sufficientarian Functions
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    Chapter 16 An Alternative to Power Measure for Fuzzy Rule-Based Classification Systems
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    Chapter 17 FT-BlinGui: A Fuzzy-Based Wearable Device System to Avoid Visually Impaired Collision in Real Time
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    Chapter 18 Genetic Learning Analysis of Fuzzy Rule-Based Classification Systems Considering Data Reduction
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    Chapter 19 Towards a Theory of Hyperintensional Belief Change
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    Chapter 20 An Online Pyramidal Embedding Technique for High Dimensional Big Data Visualization
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    Chapter 22 Particle Competition for Unbalanced Community Detection in Complex Networks
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    Chapter 23 2CS: Correlation-Guided Split Candidate Selection in Hoeffding Tree Regressors
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    Chapter 24 A Distance-Weighted Selection of Unlabelled Instances for Self-training and Co-training Semi-supervised Methods
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    Chapter 25 Active Learning Embedded in Incremental Decision Trees
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    Chapter 26 Link Prediction in Social Networks: An Edge Creation History-Retrieval Based Method that Combines Topological and Contextual Data
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    Chapter 27 Predicting the Evolution of COVID-19 Cases and Deaths Through a Correlations-Based Temporal Network
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    Chapter 28 Decoding Machine Learning Benchmarks
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    Chapter 29 Towards an Instance-Level Meta-learning-Based Ensemble for Time Series Classification
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    Chapter 30 Ensemble of Binary Classifiers Combined Using Recurrent Correlation Associative Memories
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    Chapter 31 Comparative Study of Fast Stacking Ensembles Families Algorithms
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    Chapter 32 KNN Applied to PDG for Source Code Similarity Classification
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    Chapter 33 Measuring Instance Hardness Using Data Complexity Measures
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    Chapter 34 Simulating Complexity Measures on Imbalanced Datasets
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    Chapter 35 SSL-C4.5: Implementation of a Classification Algorithm for Semi-supervised Learning Based on C4.5
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    Chapter 36 Data Streams Are Time Series: Challenging Assumptions
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    Chapter 37 Evaluating a New Approach to Data Fusion in Wearable Physiological Sensors for Stress Monitoring
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    Chapter 38 Financial Time Series Forecasting via CEEMDAN-LSTM with Exogenous Features
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    Chapter 39 Improved Multilevel Algorithm to Detect Communities in Flight Networks
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    Chapter 40 Intelligent Classifiers on the Construction of Pollution Biosensors Based on Bivalves Behavior
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    Chapter 41 New Adaptive Morphological Geodesic Active Contour Method for Segmentation of Hemorrhagic Stroke in Computed Tomography Image
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    Chapter 42 Parallel Monte Carlo Tree Search in General Video Game Playing
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    Chapter 43 Photovoltaic Generation Forecast: Model Training and Adversarial Attack Aspects
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    Chapter 44 Quantifying Temporal Novelty in Social Networks Using Time-Varying Graphs and Concept Drift Detection
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    Chapter 45 Stocks Clustering Based on Textual Embeddings for Price Forecasting
Attention for Chapter 45: Stocks Clustering Based on Textual Embeddings for Price Forecasting
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Chapter title
Stocks Clustering Based on Textual Embeddings for Price Forecasting
Chapter number 45
Book title
Intelligent Systems
Published by
Springer, Cham, October 2020
DOI 10.1007/978-3-030-61380-8_45
Book ISBNs
978-3-03-061379-2, 978-3-03-061380-8
Authors

André D. C. M. de Oliveira, Pedro F. A. Pinto, Sergio Colcher, de Oliveira, André D. C. M., Pinto, Pedro F. A., Colcher, Sergio

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The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 17 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 17 100%

Demographic breakdown

Readers by professional status Count As %
Unspecified 2 12%
Student > Doctoral Student 2 12%
Professor 2 12%
Student > Ph. D. Student 2 12%
Researcher 2 12%
Other 2 12%
Unknown 5 29%
Readers by discipline Count As %
Business, Management and Accounting 4 24%
Unspecified 2 12%
Economics, Econometrics and Finance 2 12%
Computer Science 2 12%
Mathematics 1 6%
Other 0 0%
Unknown 6 35%