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Titlebook: Nature-Inspired Computation and Machine Learning; 13th Mexican Interna Alexander Gelbukh,Félix Castro Espinoza,Sofía N. G Conference procee

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發(fā)表于 2025-3-21 19:42:21 | 只看該作者 |倒序?yàn)g覽 |閱讀模式
書目名稱Nature-Inspired Computation and Machine Learning
副標(biāo)題13th Mexican Interna
編輯Alexander Gelbukh,Félix Castro Espinoza,Sofía N. G
視頻videohttp://file.papertrans.cn/663/662066/662066.mp4
叢書名稱Lecture Notes in Computer Science
圖書封面Titlebook: Nature-Inspired Computation and Machine Learning; 13th Mexican Interna Alexander Gelbukh,Félix Castro Espinoza,Sofía N. G Conference procee
描述The two-volume set LNAI 8856 and LNAI 8857 constitutes the proceedings of the 13th Mexican International Conference on Artificial Intelligence, MICAI 2014, held in Tuxtla, Mexico, in November 2014. The total of 87 papers plus 1 invited talk presented in these proceedings were carefully reviewed and selected from 348 submissions. The first volume deals with advances in human-inspired computing and its applications. It contains 44 papers structured into seven sections: natural language processing, natural language processing applications, opinion mining, sentiment analysis, and social network applications, computer vision, image processing, logic, reasoning, and multi-agent systems, and intelligent tutoring systems. The second volume deals with advances in nature-inspired computation and machine learning and contains also 44 papers structured into eight sections: genetic and evolutionary algorithms, neural networks, machine learning, machine learning applications to audio and text, data mining, fuzzy logic, robotics, planning, and scheduling, and biomedical applications.
出版日期Conference proceedings 2014
關(guān)鍵詞affective computing; autonomous agents; biometrics; computer vision; distributed systems; evolutionary co
版次1
doihttps://doi.org/10.1007/978-3-319-13650-9
isbn_softcover978-3-319-13649-3
isbn_ebook978-3-319-13650-9Series ISSN 0302-9743 Series E-ISSN 1611-3349
issn_series 0302-9743
copyrightSpringer International Publishing Switzerland 2014
The information of publication is updating

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發(fā)表于 2025-3-21 23:55:26 | 只看該作者
A?Multi-objective?Genetic?Algorithm for the Software?Project?Scheduling?Probleming the project on time. Recent research takes into account that each employee is proficient in some development tasks only, which requiere specific skills. However, this cannot be totally applied in the Mexican context due to software companies do not categorize their employees by software skills,
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Extension of the Method of Musical Composition for the Treatment of Multi-objective Optimization Proithm, the Method of Musical Composition (MMC). The MMC uses a society of agents, called composers, who have their own creative ability, maintain a memory of their previous artwork and are also able to exchange information..According to this analogy, a decomposition approach implemented through a Tch
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發(fā)表于 2025-3-22 12:44:47 | 只看該作者
k-Nearest-Neighbor by Differential Evolution for Time Series ForecastingNNDEF (Nearest Neighbor - Differential Evolution Forecasting) is based on knowledge shared from nearest neighbors with previous similar behaviour, which are then taken into account to forecast. NNDEF relies on the assumption that observations in the past similar to the present ones are also likely t
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發(fā)表于 2025-3-22 16:10:56 | 只看該作者
A Binary Differential Evolution with Adaptive Parameters Applied to the Multiple Knapsack Problemtes. The well-known 0-1 Multiple Knapsack Problem (MKP) is addressed to validate the performance of the method. The MKP is a NP-hard optimization problem and the aim is to maximize the total profit subjected to the total weight in each knapsack that must be less than or equal to a given limit. Resul
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發(fā)表于 2025-3-22 17:22:44 | 只看該作者
Voting Algorithms Model with a Support Sets System by Class features subsets as support to classify a new object, which is called support set system. Each support set consists of selected features that are intended to discriminate the class of each object in the learning matrix. In this paper, a new model called AlVot By Class (AlVot BC) is proposed. It is
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發(fā)表于 2025-3-23 07:43:06 | 只看該作者
Feature Analysis for the Classification of Volcanic Seismic Events Using Support Vector Machineses in South America.?1622 classified events registered from the Llaima volcano were considered in this study, taken from 2009 to 2011. The events were divided in four classes: TREMOR (TR), LONG-PERIOD (LP), VOLCANO-TECTONICS (VT) and OTHERS (OT). All of them correspond to specific activities. TR and
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