Objectivies: SVM is Mainly established for linear multi-class classification through building a finest splitting hyperplane, here the scope is maximized. SVM is useful for core deception to plot the novel key in space into a high dimensional attribute slot to improve the classifier generality ability when the training data is not linear splitable. Methods/Analysis: GA is a speculator and the em...

-Generating association rules is generally done by association rule mining algorithm like classical algorithm Apriori, FP-Tree Partition and so on. Genetic algorithm can also implement to generate association rules. Main advantage of Genetic algorithm is that it can perform global search. This paper presents proposed algorithm Multi-Fitness function Genetic algorithm (MFGA) based association ru...

multifunctional nanomaterials showed graet advantages in drug delivery. folic acid (fa) binding protein, a glycosyl phosphatidyl inositol anchored cell surface receptor for folate, is overexpressed in several human tumors, whereas it is highly restricted in normal tissues. therefore, in this study, fa, polyethylene glycol (peg), and fe3o4 nanoparticles multifunctionalized short multiwall carbon...

We sketch a novel and improved version of Boorse’s biostatistical theory of functions. Roughly, our theory maintains that (i) functions are non-negligible contributions to survival or inclusive fitness (when a trait contributes to survival or inclusive fitness); (ii) situations appropriate for the performance of a function are typical situations in which a trait contributes to survival or inclu...

An evolutionary algorithm is used to design a digital filter with reduced power consumption. The proposed design approach combines genetic optimisation and simulation methodology, to evaluate a multi-objective fitness function which includes both the suitability of the filter transfer function and the transition activity of digital blocks. A client-server computer program allows the user to exp...

This paper presents a Genetic algorithm based association rule mining in which multi fitness functions are used. Genetic algorithm is used for performing global search. This proposed algorithm generates intersecting association rules from dataset. A fitness function with parameter support is defined for generating frequent itemsets and then other parameters like confidence, lift, leverage etc a...

In this paper we introduce the variable fitness function which can be used to control the search direction of any search based optimisation heuristic where more than one objective can be defined, to improve heuristic performance. The method is applied to a multi-objective travelling salesman problem and the performance of heuristics enhanced with the variable fitness function is compared to the...

This paper presents a Genetic algorithm based association rule mining in which multi fitness functions are used. Genetic algorithm is used for performing global search. This proposed algorithm generates intersecting association rules from dataset. A fitness function with parameter support is defined for generating frequent itemsets and then other parameters like confidence, lift, leverage etc a...