Abstract: Natural light is an important factor that needs to be considered in the implementation of an automatic sprayer system. This paper evaluates the scalability of real time specific weed recognition system using histogram analysis, and its comparison with two dimensional weed coverage rate (2DWCR), and Angular Cross Sectional Intensities (ACSI) classifiers based on the variation in the natural lighting conditions to encompass the cloudy and bright shiny outdoor environment. A large image dataset of 1500 images was used as compared to the previously used image datasets (200-1200 image datasets). The dataset images are further subdivided based on different lighting conditions and is termed as normal, dark, and bright. The proposed classifier was applied to classify these images into broad and narrow class for real time selective herbicide application using a single constant threshold. The analysis of the results shows over 94 percent weeds detection and classification accuracy (broad and nar

• Publication Date: 11-Oct-2015
• DOI: 10.15224/978-1-63248-064-4-117
• Views: 0
• Downloads: 0

Abstract: Proposing a multi-objective method is a common part of the process of supporting the decision-making process in population problems. This with the goal of motivating the selection of projects that help the population sector that has scarce water and drainage services at home. The method should provide a set of solutions that reflect the urgency to attend this population sector. Each solution is a set of geographical zone partitions formed by geographical units that fulfill the geometric compactness and homogeneity criteria, this homogeneity is given by the variable named "private houses without tap water, drainage network nor electricity services". We present basic theoretical aspects about the multiobjective methodology and a method supported on the order theory to find the Pareto Frontier. Given that the problem solves a kind of partitioning that optimizes two quality measures, the approximation to the optimal solution is made with variable neighborhood search (VNS). Once we obtained

• Publication Date: 11-Oct-2015
• DOI: 10.15224/978-1-63248-064-4-125
• Views: 0
• Downloads: 0