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Literature presents several search algorithms to find an item with specified properties from a search space defined by a mathematical formula or procedure. One of the widely accepted algorithms is optimization algorithm which can find the optimal element within a certain period of time if the search space is defined. Recent works formulate several problems as optimization problems which were then solved by many optimization algorithms. Accordingly, in a previous paper, a hybrid optimization algorithm, called FAGA was proposed using fractional order Artificial Bee Colony (ABC) and Genetic Algorithm (GA) for optimization to solve the existing benchmark problems. In this paper, we have planned to apply the FAGA algorithm to well defined-real time problems of neural network training and the clustering process. Through neural network training, data classification will be done by making use of FAGA algorithm as neural network training procedure. Similarly, medical image segmentation will be done using clustering process through FAGA algorithm. The performance of the FAGA algorithm in those two processes will be evaluated with different evaluation metrics and the comparison of the FAGA algorithm will be also carried out with the existing ABC and genetic algorithm.

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Major catalysts, e.g. deregulation, global competition, technological breakthroughs, changing customer expectations, structural changes, excess capacity, environmental concerns, less protectionism, etc., are reshaping the landscape of corporations worldwide. Assumptions about predictability, stability and clear boundaries are becoming less valid as two key actors have a clear impact on the nature of competitive space: agents with knowledge and interactions. IJIE covers new concepts of strategy and organisation as competitiveness of companies increasingly depends upon exploiting the new strategic potentials of intellect/service technologies. Contents: IJIE publishes high-quality original papers and it is double blind peer-reviewed. It presents strategies, resources, methodologies, tools, and techniques, aimed to unfold key aspects related to intellect and service technologies, relevant for research and practice. Both theoretical and empirical papers are welcome as well as qualitative and quantitative studies. Special Issues devoted to important topics within the aims and scopes of the Journal are also considered.