In today’s era Big data classification is a very crucial and equally widely arise issue many applications. Not only engineering applications but also in social, agricultural, banking, educational more are there science where accurate big required. We proposed novel efficient methodology for using Deep stack encoder Rider chaotic biogeography algorithms. Our algorithms the combinations of two Fi...

Biogeography-Based Optimization (BBO) is a recently conceived bio-inspired optimization technique and population based evolutionary algorithm (EA). It mainly uses the idea of probabilistically sharing features between solutions based on the solutions’ fitness values. Due to this feature, its exploitation ability is good. In this paper, we have demonstrated the performance of BBO for block motio...

Emergency transportation plays a vital role in the success of disaster rescue and relief operations, but its planning and scheduling often involve complex objectives and search spaces. In this paper, we conduct a survey of recent advances in bio-inspired meta-heuristics, including genetic algorithms (GA), particle swarm optimization (PSO), ant colony optimization (ACO), etc., for solving emerge...

We present hardware testing of an evolutionary algorithm known as biogeography-based optimization (BBO) and extend it to distributed learning. BBO is an evolutionary algorithm based on the theory of biogeography, which describes how nature geographically distributes organisms. We introduce a new BBO algorithm that does not use a centralized computer, and which we call dis­ tributed BBO. BBO and...

“Segmentation” refers to the process of dividing a digital image into multiple segments such as sets of pixels, also known as super pixels. The main objective of segmentation is to simplify and/or change the representation of an image into meaningful image that is more appropriate and easier to analyze. “Image segmentation” is an important aspect of digital image processing. Color images can in...