Classification of different deadly diseases using machine learning algorithms helps in making the health care system more robust. This, not only reduces human errors during diagnosis disease due to inexperience but also physician for taking an emergency action earlier biopsy. As genomic data undergoes through malediction excessive dimension problem, both selection remarkable genes and classific...

The execution of scientific applications needs high-processing computers and requires massive storage. This resulted in deploying a distributed environment with high performance extensive Applications processed cloud platforms face intolerable delays due to data movement across the centres. Optimized distribution datasets among global centres has become an essential issue environment. work prop...

In the past few years nature-inspired algorithms are experiencing rapid growth where most optimisation problems in different domains addressed using it. As a result of this development come issue handling complex problem within short period remains very difficult. Symbiotic organisms search (SOS) algorithm is one metaheuristics that mimics symbiotic association an ecosystem. This paper proposes...

scheduling is to determine the priorities or arrange the activities to meet the needs, limitations and certain goals. because the time is always a limited resource, all activities should be scheduled to use optimally and certainly the resource. gravitational force algorithm, like other evolutionary algorithms, is inspired by nature. the effect of the gravity on the objects reciprocally and to a...

The steganography is applied on text, image, video, and audio files. useful for safe secure data transmission. Video used to preserve confidential information of security applications. To improve the message, pixels locations are optimized using nature inspired algorithm. As conventional algorithms have a low convergence rate new algorithm proposed. A New developed by combining two model namely...

Nature inspired meta-heuristic algorithms are iterative search processes which find near optimal solutions by efficiently performing exploration and exploitation of the solution space. Considering the solution space in a specified region, this work compares performances of Bat, Cuckoo search and Firefly algorithms for unconstrained optimization problems. Global optima are found using various te...

Artificial Bee Colony (ABC) optimization algorithm is a swarm intelligence based nature inspired algorithm which has been proved a competitive algorithm with some popular nature-inspired algorithms. However, it is found that the ABC algorithm prefers exploration at the cost of the exploitation. Therefore, in this paper a self adaptive fitness based mutation strategy is presented in which the pe...