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Titlebook: Computational Collective Intelligence; 7th International Co Manuel Núñez,Ngoc Thanh Nguyen,Bogdan Trawiński Conference proceedings 2015 Spr

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Springer Monographs in Mathematicstactic-semantic knowledge that they contain. Furthermore, we evaluated our proposal with the cross validation method by using 690 pairs of sentences taken from old Arabic dictionaries designed for human use like Al-Wassit and Lissan-Al-Arab. The obtained results are very encouraging and show a good performance that approximates to human intuition.
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A Model of a Multiagent Early Warning System for Crisis Situations in Economy multiagent early warning system for crisis situations in economy. The system will include all branches of economy, and it may be used by any group of users. It will have the ability to predict unfavorable economic situations at a local, scattered, and integral level.
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Supervised Learning to Measure the Semantic Similarity Between Arabic Sentencestactic-semantic knowledge that they contain. Furthermore, we evaluated our proposal with the cross validation method by using 690 pairs of sentences taken from old Arabic dictionaries designed for human use like Al-Wassit and Lissan-Al-Arab. The obtained results are very encouraging and show a good performance that approximates to human intuition.
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Conference proceedings 2015 in biomedicine; collective computational intelligence in educational context; science intelligence and data analysis; computational intelligence in financial markets; ensemble learning; big data mining and searching.
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Structure and Properties of Liquid Crystalss to provide means to bring the AMAS design to a higher stage of automation and confidence thanks to Simulation. ADELFE 3.0 is a new version of ADELFE based on a Simulation Based Design approach in order to assist the designer of AMAS and make his task less difficult. This paper focuses on a practical example of building an AMAS using ADELFE 3.0.
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Magnetic, Electric and Transport Propertiesn (CRO) to solve the FJSP in order to minimize the maximum completion time (makespan). Experiments are performed on benchmark instances proposed in the literature to evaluate the performance of our model.
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