Swam intelligence is an emerging field in Artificial Intelligence. The living nature and life style of animals, birds and other living organisms can be inherited and applied to solve many real world problems. ABC is a recently developed swam intelligence algorithm developed by Dervis Karaboga in the year 2005.In ABC, foraging is one of the behavior of honey bees to search, collect food from its...

Microarray gene expression data can be analyzed for diagnosis of cancer and its stage. It usually concerns a very large number of variables relative to a small number of observations. This makes application of data mining techniques difficult and so to reduce the data dimensionality some pre-processing technique needs to be used. In this paper dataset used for analysis is about lung cancer cons...

The hybrid of Differential Evolution algorithm with Kalman Filtering and Bacterial Foraging algorithm is a novel global optimization method that is implemented in this research to obtain the best kinetic parameter value. The proposed algorithm is then used to model tyrosine production in mus musculus (mouse) by using a dataset, JAK/STAT (Janus Kinase Signal Transducer and Activator of Transcrip...

Feature selection (FS) is a global optimization problem in machine learning, which reduces the number of features, removes irrelevant, noisy and redundant data, and results in acceptable recognition accuracy. This paper presents a novel feature selection algorithm based on Bacteria Foraging Optimization (BFO). The algorithm is applied to coefficients extracted by discrete cosine transforms (DCT...

This paper proposes a neuro-fuzzy filter for equalization of time-varying channels. Additionally, it proposes to tune the equalizer with a hybrid algorithm between Genetic Algorithms (GA) and Bacteria Foraging (BFO), termed as GBF. The major advantage of the method developed in this paper is that all parameters of the neuro-fuzzy network, including the rule base, are tuned simultaneously throug...

Eliminating noise from the original image is still a challenging task for researchers. Several algorithms have been proposed and each of them has its own assumptions, advantages & limitations. The paper proposes the noise reduction method for the medical images by using Hybrid BFO i.e the fusion of BFO (Bacteria foraging optimization) and the technique of contourlet transform and the results ar...

Robust face recognition and classification has been an area of interest for researchers in many disciplines of science and engineering. In this paper, we present a new technique for designing optimal filters for face classification using the bacteria foraging algorithm. The simulation results show that the optimal filter is able to classify the face images correctly into the target and anti-tar...

-The most important task in digital image processing is image segmentation. This paper put forward an unique image segmentation algorithm that make use of a Markov Random Field (MRF) hybrid with biologically inspired technique Bacteria Foraging Optimization Algorithm (BFOA) for Brain Magnetic Resonance Images The proposed new algorithm works on the image pixel data and a region/neighborhood map...