# Artificial Intelligence and Soft Computing: 17th International Conference, Part I

- Length: 774 pages
- Edition: 1st ed. 2018
- Language: English
- Publisher: Springer
- Publication Date: 2018-06-17
- ISBN-10: 3319912526
- ISBN-13: 9783319912523
- Sales Rank: #9119861 (See Top 100 Books)

Artificial Intelligence and Soft Computing: 17th International Conference, ICAISC 2018, Zakopane, Poland, June 3-7, 2018, Proceedings, Part I (Lecture Notes in Computer Science)

The two-volume set LNAI 10841 and LNAI 10842 constitutes the refereed proceedings of the 17th International Conference on Artificial Intelligence and Soft Computing, ICAISC 2018, held in Zakopane, Poland in June 2018.

The 140 revised full papers presented were carefully reviewed and selected from 242 submissions. The papers included in the first volume are organized in the following three parts: neural networks and their applications; evolutionary algorithms and their applications; and pattern classification.

### Table of Contents

Chapter 1. Three-Dimensional Model of Signal Processing in the Presynaptic Bouton of the Neuron

Chapter 2. The Parallel Modification to the Levenberg-Marquardt Algorithm

Chapter 3. On the Global Convergence of the Parzen-Based Generalized Regression Neural Networks Applied to Streaming Data

Chapter 4. Modelling Speaker Variability Using Covariance Learning

Chapter 5. A Neural Network Model with Bidirectional Whitening

Chapter 6. Block Matching Based Obstacle Avoidance for Unmanned Aerial Vehicle

Chapter 7. Prototype-Based Kernels for Extreme Learning Machines and Radial Basis Function Networks

Chapter 8. Supervised Neural Network Learning with an Environment Adapted Supervision Based on Motivation Learning Factors

Chapter 9. Autoassociative Signature Authentication Based on Recurrent Neural Network

Chapter 10. American Sign Language Fingerspelling Recognition Using Wide Residual Networks

Chapter 11. Neural Networks Saturation Reduction

Chapter 12. Learning and Convergence of the Normalized Radial Basis Functions Networks

Chapter 13. Porous Silica-Based Optoelectronic Elements as Interconnection Weights in Molecular Neural Networks

Chapter 14. Data Dependent Adaptive Prediction and Classification of Video Sequences

Chapter 15. Multi-step Time Series Forecasting of Electric Load Using Machine Learning Models

Chapter 16. Deep Q-Network Using Reward Distribution

Chapter 17. Motivated Reinforcement Learning Using Self-Developed Knowledge in Autonomous Cognitive Agent

Chapter 18. Company Bankruptcy Prediction with Neural Networks

Chapter 19. Soft Patterns Reduction for RBF Network Performance Improvement

Chapter 20. An Embedded Classifier for Mobile Robot Localization Using Support Vector Machines and Gray-Level Co-occurrence Matrix

Chapter 21. A New Method for Learning RBF Networks by Utilizing Singular Regions

Chapter 22. Cyclic Reservoir Computing with FPGA Devices for Efficient Channel Equalization

Chapter 23. Discrete Cosine Transform Spectral Pooling Layers for Convolutional Neural Networks

Chapter 24. Extreme Value Model for Volatility Measure in Machine Learning Ensemble

Chapter 25. Deep Networks with RBF Layers to Prevent Adversarial Examples

Chapter 26. Application of Reinforcement Learning to Stacked Autoencoder Deep Network Architecture Optimization

Chapter 27. An Optimization Algorithm Based on Multi-Dynamic Schema of Chromosomes

Chapter 28. Eight Bio-inspired Algorithms Evaluated for Solving Optimization Problems

Chapter 29. Robotic Flow Shop Scheduling with Parallel Machines and No-Wait Constraints in an Aluminium Anodising Plant with the CMAES Algorithm

Chapter 30. Migration Model of Adaptive Differential Evolution Applied to Real-World Problems

Chapter 31. Comparative Analysis Between Particle Swarm Optimization Algorithms Applied to Price-Based Demand Response

Chapter 32. Visualizing the Optimization Process for Multi-objective Optimization Problems

Chapter 33. Comparison of Constraint Handling Approaches in Multi-objective Optimization

Chapter 34. Genetic Programming for the Classification of Levels of Mammographic Density

Chapter 35. Feature Selection Using Differential Evolution for Unsupervised Image Clustering

Chapter 36. A Study on Solving Single Stage Batch Process Scheduling Problems with an Evolutionary Algorithm Featuring Bacterial Mutations

Chapter 37. -1Observation of Unbounded Novelty in Evolutionary Algorithms is Unknowable

Chapter 38. Multi-swarm Optimization Algorithm Based on Firefly and Particle Swarm Optimization Techniques

Chapter 39. New Running Technique for the Bison Algorithm

Chapter 40. Evolutionary Design and Training of Artificial Neural Networks

Chapter 41. Obtaining Pareto Front in Instance Selection with Ensembles and Populations

Chapter 42. Negative Space-Based Population Initialization Algorithm (NSPIA)

Chapter 43. Deriving Functions for Pareto Optimal Fronts Using Genetic Programming

Chapter 44. Identifying an Emotional State from Body Movements Using Genetic-Based Algorithms

Chapter 45. Particle Swarm Optimization with Single Particle Repulsivity for Multi-modal Optimization

Chapter 46. Hybrid Evolutionary System to Solve Optimization Problems

Chapter 47. Horizontal Gene Transfer as a Method of Increasing Variability in Genetic Algorithms

Chapter 48. Evolutionary Induction of Classification Trees on Spark

Chapter 49. How Unconventional Chaotic Pseudo-Random Generators Influence Population Diversity in Differential Evolution

Chapter 50. An Adaptive Individual Inertia Weight Based on Best, Worst and Individual Particle Performances for the PSO Algorithm

Chapter 51. A Mathematical Model and a Firefly Algorithm for an Extended Flexible Job Shop Problem with Availability Constraints

Chapter 52. On the Prolonged Exploration of Distance Based Parameter Adaptation in SHADE

Chapter 53. Investigating the Impact of Road Roughness on Routing Performance: An Evolutionary Algorithm Approach

Chapter 54. Integration Base Classifiers in Geometry Space by Harmonic Mean

Chapter 55. Similarity of Mobile Users Based on Sparse Location History

Chapter 56. Medoid-Shift for Noise Removal to Improve Clustering

Chapter 57. Application of the Bag-of-Words Algorithm in Classification the Quality of Sales Leads

Chapter 58. Probabilistic Feature Selection in Machine Learning

Chapter 59. Boost Multi-class sLDA Model for Text Classification

Chapter 60. Multi-level Aggregation in Face Recognition

Chapter 61. Direct Incorporation of L1-Regularization into Generalized Matrix Learning Vector Quantization

Chapter 62. Classifiers for Matrix Normal Images: Derivation and Testing

Chapter 63. Random Projection for k-means Clustering

Chapter 64. Modified Relational Mountain Clustering Method

Chapter 65. Relative Stability of Random Projection-Based Image Classification

Chapter 66. Cost Reduction in Mutation Testing with Bytecode-Level Mutants Classification

Chapter 67. Probabilistic Learning Vector Quantization with Cross-Entropy for Probabilistic Class Assignments in Classification Learning

Chapter 68. Multi-class and Cluster Evaluation Measures Based on Rényi and Tsallis Entropies and Mutual Information

Chapter 69. Verification of Results in the Acquiring Knowledge Process Based on IBL Methodology

Chapter 70. A Fuzzy Measure for Recognition of Handwritten Letter Strokes