Factual power loss reduction by enriched black hole algorithm

This paper presents enriched black hole algorithm (EBHA) for solving optimal reactive power problem. In this work black hole algorithm based on membrane computing is projected. In black hole algorithm evolution of the population is through pushing the candidates in the course of the most excellent candidate in iterations and black hole which swap with those in the search space. Membrane computing is also branded as P system and it has multisets of objects with evolution rules in the membrane structure. Membrane structure is alike ingrained tree of section that demarcate the areas, and root is labelled as skin. Chemical substances (multisets of objects) are there inside the section (membranes) of a cell and the chemical reactions (evolution rules) that take place within the cell. Proposed enriched black hole algorithm (EBHA) has been evaluated in IEEE 14,300 bus test system. Loss reduction achieved.

Iris Segmentation Based on Black Hole Algorithm for Biometric System

Current iris recognition schemes such as IntegroDifferential method, Hough Transform, Watershed Transform Circle Fitting, and Circular Hough Transformation (CHT) are used to find circular parameters between pupil and iris. Segmentation process of an eye image using the circular parameters toextracts the iris region still can be further improved. In this paper, we introduced an optimization method of circular parameters detection for iris segmentation based on Black Hole Algorithm (BHA). The proposed segmentation algorithm utilizes a computational model of the pixels’ value to detect the iris boundary. The BHA searches for center radius of both pupil and iris. The system tests the CASIA Iris Interval V3 database by on MATLAB. The segmented images show an accuracy of 98.3%. In short, the segmentation-based on BHA is efficient to identify the iris for any future access control applications.