Optimization of Herbal Drugs using Soft Computing Approach
نویسندگان
چکیده
The study presents the results of our investigation into the use of Genetic Algorithms (GA) and Artificial Neural Network (ANN) for identifying near optimal design parameters of compositions of drug systems that are based on soft computing approach for herbal drug design. Herbal medicine has been applied successfully in much clinical practices since long throughout in world. The present study proposes a novel concept using a computational technique to predict bioactivity of herbal drug and designing of new herbal drug for a particular disease. Genetic algorithm investigated the relationship between chemical composition of a widely used herbal medicine in India and its bioactivity effect. The predicted bioactivity with respect to its composition indicates that the proposed computing method is an efficient tool to herbal drug design.
منابع مشابه
Utilization of Soft Computing for Evaluating the Performance of Stone Sawing Machines, Iranian Quarries
The escalating construction industry has led to a drastic increase in the dimension stone demand in the construction, mining and industry sectors. Assessment and investigation of mining projects and stone processing plants such as sawing machines is necessary to manage and respond to the sawing performance; hence, the soft computing techniques were considered as a challenging task due to stocha...
متن کاملTRANSPORT ROUTE PLANNING MODELS BASED ON FUZZY APPROACH
Transport route planning is one of the most important and frequent activities in supply chain management. The design of information systems for route planning in real contexts faces two relevant challenges: the complexity of the planning and the lack of complete and precise information. The purpose of this paper is to nd methods for the development of transport route planning in uncertainty dec...
متن کاملA COMPARATIVE STUDY OF TRADITIONAL AND INTELLIGENCE SOFT COMPUTING METHODS FOR PREDICTING COMPRESSIVE STRENGTH OF SELF – COMPACTING CONCRETES
This study investigates the prediction model of compressive strength of self–compacting concrete (SCC) by utilizing soft computing techniques. The techniques consist of adaptive neuro–based fuzzy inference system (ANFIS), artificial neural network (ANN) and the hybrid of particle swarm optimization with passive congregation (PSOPC) and ANFIS called PSOPC–ANFIS. Their perf...
متن کاملSoft Computing Based on a Modified MCDM Approach under Intuitionistic Fuzzy Sets
The current study set to extend a new VIKOR method as a compromise ranking approach to solve multiple criteria decision-making (MCDM) problems through intuitionistic fuzzy analysis. Using compromise method in MCDM problems contributes to the selection of an alternative as close as possible to the positive ideal solution and far away from the negative ideal solution, concurrently. Using Atanasso...
متن کاملAn Effective Task Scheduling Framework for Cloud Computing using NSGA-II
Cloud computing is a model for convenient on-demand user’s access to changeable and configurable computing resources such as networks, servers, storage, applications, and services with minimal management of resources and service provider interaction. Task scheduling is regarded as a fundamental issue in cloud computing which aims at distributing the load on the different resources of a distribu...
متن کامل