文件名称：Artificial.Intelligence.and.Soft.Computing.17th.International.Conference.Part.I
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更新时间：2021-06-19 03:11:38
人工智能 算法
各种新算法研究，没有足够的数学和英语基础就别下载了。 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