Advances in Soft Computing and Its Applications: 12th - download pdf or read online

By Angel Kuri-Morales, Edwin Aldana-Bobadilla (auth.), Félix Castro, Alexander Gelbukh, Miguel González (eds.)

ISBN-10: 3642451101

ISBN-13: 9783642451102

ISBN-10: 364245111X

ISBN-13: 9783642451119

The two-volume set LNAI 8265 and LNAI 8266 constitutes the complaints of the twelfth Mexican overseas convention on man made Intelligence, MICAI 2013, held in Mexico urban, Mexico, in November 2013. the whole of eighty five papers awarded in those court cases have been conscientiously reviewed and chosen from 284 submissions. the 1st quantity offers with advances in synthetic intelligence and its functions and is based within the following 5 sections: good judgment and reasoning; knowledge-based structures and multi-agent structures; ordinary language processing; desktop translation and bioinformatics and clinical purposes. the second one quantity bargains with advances in tender computing and its purposes and is established within the following 8 sections: evolutionary and nature-inspired metaheuristic algorithms; neural networks and hybrid clever structures; fuzzy platforms; desktop studying and development reputation; info mining; laptop imaginative and prescient and photo processing; robotics, making plans and scheduling and emotion detection, sentiment research and opinion mining.

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Additional info for Advances in Soft Computing and Its Applications: 12th Mexican International Conference on Artificial Intelligence, MICAI 2013, Mexico City, Mexico, November 24-30, 2013, Proceedings, Part II

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Generate a random binary string. This is one possible f i ( x) . 3. Minimize f i ( x) iterating A, G times. 4. 5. Store the best minimum value κ i . Repeat steps (2-4) 36 times. F. Kuri-Morales, E. Aldana-Bobadilla, and I. López-Peña 6. Calculate the average best value κ j= (1 / 36) 36 κ . i =1 i 7. 8. 9. 10. Repeat steps (5-6) 50 times. Calculate μκ and σ κ . Repeat step (7) 85 times. 95. Calculate μ = μ κ and σ = 6 σ κ . We have inferred the expected best value κ and the standard deviation for this algorithm.

C Springer-Verlag Berlin Heidelberg 2013 The Concept of Confidence for Inheritance-Based Genetic Algorithms 31 article the exploration of promising ways to make an efficient search with some given M N computation time. This work is organized in the following manner: In the first part, the concept of inheritance is introduced. Then the concept of confidence is proposed as a way to improve inheritance performance. Then, confidence-based schemes are presented. In the second part, the GA and the inheritance-based algorithms are compared with the use of benchmark problems.

We thusly calculate 100,000 combinations of size NS. Out of these combinations we count those for which χ 2 ≤ χ best AND there are at least omin =5 observations per decile. This number divided by 100,000 (which we shall call p) is the experimental probability that, for NS observations, χ 2 “performs” as required. The Best Genetic Algorithm II 21 We repeat this process increasing NS up to 100. In every instance we test whether p > P. If such is the case we decrement the value of χ best and re-start the process.

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Advances in Soft Computing and Its Applications: 12th Mexican International Conference on Artificial Intelligence, MICAI 2013, Mexico City, Mexico, November 24-30, 2013, Proceedings, Part II by Angel Kuri-Morales, Edwin Aldana-Bobadilla (auth.), Félix Castro, Alexander Gelbukh, Miguel González (eds.)


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