Download Soft Computing Models in Industrial and Environmental by Amy Neustein (auth.), Emilio Corchado, Václav Snášel, Javier PDF

By Amy Neustein (auth.), Emilio Corchado, Václav Snášel, Javier Sedano, Aboul Ella Hassanien, José Luis Calvo, Dominik Ślȩzak (eds.)

This quantity of Advances in clever and tender Computing includes approved papers awarded at SOCO 2011 held within the appealing and historical urban of Salamanca, Spain, April 2011. This quantity offers the papers approved for the 2011 version, either for the most occasion and the distinctive periods. SOCO 2011 designated classes are a really great tool on the way to supplement the usual software with new or rising issues of specific curiosity to the partaking neighborhood. 4 detailed periods have been geared up regarding proper themes as: Optimization and regulate in undefined, Speech Processing and delicate Computing, platforms, guy & Cybernetics and tender Computing for scientific Applications.

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Additional info for Soft Computing Models in Industrial and Environmental Applications, 6th International Conference SOCO 2011

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Keywords: White grape detection, visual inspection, image processing, precision viticulture. 1 Introduction The concept of Precision Agriculture (PA) and Precision Viticulture (PV) is based on new tools and information sources provided by modern technologies, such as yield monitoring devices, soil, plant and pest sensors and remote sensing. It promotes Manuel Cabral Reis · Salviano Soares · A. pt Carlos Pereira · J. B. G. Ferreira IEETA, Campus Univ. pt E. Corchado et al. ): SOCO 2011, AISC 87, pp.

Section 5 is devoted to the conclusions and future work. 2 DDR Unique Characteristics and Their Impact on the System The DDR (a UNESCO World Heritage Site and the oldest Wine Demarcated Region of the World), due to its unique characteristics, poses very specific challenges, mainly due to the topographic profile, pronounced climatic variations and complex soil characteristics. It is located in northeast Portugal, and consists mostly of steep hills (slopes reaching 15%) and narrow valleys that flatten out into plateaux above 400m.

K. , ( f itness). In general the position of ith food source is represented as Xi = (xi1 , xi2 , . . , xiD ). After the information is shared by the employed bees, online bees goes to the region of food source at Xi based on the probability Pi defined as pi = f iti f itk ∑FS k=1 where FS is total number of food sources. Fitness value f iti is calculated by using following equation. f iti = 1 1 + f (Xi ) here f (Xi ) is the objective function in our problem ITAE. The onlooker finds its food source in the region of Xi by using following equation.

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