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Educational guide | |||||||||||||||||||||||||||||||||||||||
| IDENTIFYING DATA | 2024_25 | |||||||||||||||||||||||||||||||||||||||
| Subject | NEURAL AND EVOLUTIONAL COMPUTATION | Code | 00709029 | |||||||||||||||||||||||||||||||||||||
| Study programme |
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| Descriptors | Credit. | Type | Year | Period | ||||||||||||||||||||||||||||||||||||
| 6 | Optional | Third | Second |
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| Language |
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| Prerequisites | ||||||||||||||||||||||||||||||||||||||||
| Department | MATEMATICAS |
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| Coordinador | mcarv@unileon.es |
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| Lecturers |
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| Web | http:// | |||||||||||||||||||||||||||||||||||||||
| General description | ||||||||||||||||||||||||||||||||||||||||
| Tribunales de Revisión |
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| Competencias |
| Code | |
| A18096 | |
| A18142 | |
| A18143 | |
| B5618 | |
| B5619 | |
| B5623 | |
| B5624 | |
| B5625 | |
| C1 | CMECES1 That students have demonstrated possession and understanding of knowledge in an area of study that is based on general secondary education, and is usually found at a level that, although supported by advanced textbooks, also includes some aspects that involve knowledge from the cutting edge of their field of study |
| C4 | CMECES4 That students can transmit information, ideas, problems and solutions to both a specialised and non-specialised audience |
| C5 | CMECES5 That students have developed those learning skills necessary to undertake further studies with a high degree of autonomy |
| Learning aims |
| Competences | |||
| Shows ability to analize, of decision taking and critical reasoning | B5619 B5623 B5624 |
C5 |
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| Applies acquaried matehmatical concepts and strategies in the production of arguments hence improving the independent learning | A18096 |
B5618 |
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| Communicates in written and oral form ideas, problems and solutions through mathematical language. | B5619 B5625 |
C1 C4 |
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| Knows mathematical principles and evolutive techniques and applies them to the solution of optimization and calssification problems in the field of engineering and (bio)tecnology based on basic mathematical knowledges aquiered in previous stages | A18142 A18143 |
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| Contents |
| Topic | Sub-topic |
| PART 1: INTRODUCTION | Section 1: Basic concepts. Introduction to evolutionary computing based on biological models and mathematics tools. |
| PART II: NEURAL COMPUTING | Section 2: introcution to neural computing Section 3: Neural networks, models and applications to the resolution of problems in the field of engineering and (bio)tecnology. |
| PART III: EVOLUTIONARY COMPUTING | Part 4: Introduction to evolutionary computing Part 5: Genetic algorithms. Application to the resolution of problems in the field of engineering and (bio)technology |
| Planning |
| Methodologies :: Tests | |||||||||
| Class hours | Hours outside the classroom | Total hours | |||||||
| Problem solving, classroom exercises | 20 | 30 | 50 | ||||||
| Practicals using information and communication technologies (ICTs) in computer rooms | 20 | 20 | 40 | ||||||
| Seminars | 4 | 12 | 16 | ||||||
| Lecture | 16 | 20 | 36 | ||||||
| Extended-answer tests | 6 | 0 | 6 | ||||||
| Objective short-answer tests | 2 | 0 | 2 | ||||||
| (*)The information in the planning table is for guidance only and does not take into account the heterogeneity of the students. | |||||||||
| Methodologies |
| Description | |
| Problem solving, classroom exercises | |
| Practicals using information and communication technologies (ICTs) in computer rooms | |
| Seminars | |
| Lecture |
| Personalized attention |
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| Assessment |
| Description | Qualification | ||
| Extended-answer tests | 60% | ||
| Other comments and second call | |||
| Sources of information |
| Access to Recommended Bibliography in the Catalog ULE |
| Basic |
Haykin., Neural Networks. A comprehensive foundation. , Macmillan.1994. ,
M. Mitchell, An introduction to genetic algorithms, MIT Press (1996),
I. Nunes da Silva, D. H. Spatti, R. A. Flauzino, L. H. Bartocci Liboni e S. F. dos Reis Alves, Artificial Neural Networks. A practical course, Springer (2017),
Fausett, Fundamentals of Neural Networks. Architectures, algorithms, and applications., PrenticeHall.1994.,
Z. Michalewicz, Genetic Algorithms + Data Stuctures = Evolution programs. trd Edition, Springer-Verlag (1994),
David E. Goldberg, Genetic algorithms in search, optimization and machine learning, Addison-Wesley,
A.E. Eiben y J.E. Smith, Introduction to Evolutionary Computing, Springer (2015),
Hertz, Krogh, Palmer., Introduction to the theory of neural computation. , Addison-Wesley. 1991.,
P. Isasi Viñuela e I.M. Galván León, Redes de neuronas artificiales. Un enfoque práctico, Prentice Hall (2004),
Freeman / Skapura. 1993. , Redes Neuronales. Algoritmos, aplicaciones y técnicas de programación., , |
Notes on various topics of the course will be made available. |
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| Complementary |
M. Iglesias, B.Naudts, A. Verschoren and C. Vidal, A combinatorial approach to epistasis, Springer (2005),
R. Penrose, La Nueva Mente del Emperador, Mondadori España S.A. (1991), |
| Recommendations |
| Subjects that it is recommended to have taken before | ||||||
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