Application of evolutionary computing for hybrid model based optimization of biochemical processes
نویسندگان
چکیده
General framework for hybrid model based identification and optimization of biochemical processes is elaborated. An enhanced hybrid model of the fed-batch biosurfactant production process is presented. The evolutionary programming techniques are applied for the hybrid model identification and optimization of the process. High performance of the applied optimization techniques is reported. The perspectives of development of a software package for hybrid model based identification and optimization of biochemical processes is discussed. Key-Words: evolutionary programming, hybrid models, model based optimization, biochemical processes
منابع مشابه
Soft Computing Methods based on Fuzzy, Evolutionary and Swarm Intelligence for Analysis of Digital Mammography Images for Diagnosis of Breast Tumors
Soft computing models based on intelligent fuzzy systems have the capability of managing uncertainty in the image based practices of disease. Analysis of the breast tumors and their classification is critical for early diagnosis of breast cancer as a common cancer with a high mortality rate between women all around the world. Soft computing models based on fuzzy and evolutionary algorithms play...
متن کاملSolving Multi-objective Optimal Control Problems of chemical processes using Hybrid Evolutionary Algorithm
Evolutionary algorithms have been recognized to be suitable for extracting approximate solutions of multi-objective problems because of their capability to evolve a set of non-dominated solutions distributed along the Pareto frontier. This paper applies an evolutionary optimization scheme, inspired by Multi-objective Invasive Weed Optimization (MOIWO) and Non-dominated Sorting (NS) strategi...
متن کاملA Hybrid MOEA/D-TS for Solving Multi-Objective Problems
In many real-world applications, various optimization problems with conflicting objectives are very common. In this paper we employ Multi-Objective Evolutionary Algorithm based on Decomposition (MOEA/D), a newly developed method, beside Tabu Search (TS) accompaniment to achieve a new manner for solving multi-objective optimization problems (MOPs) with two or three conflicting objectives. This i...
متن کاملEfficient Data Mining with Evolutionary Algorithms for Cloud Computing Application
With the rapid development of the internet, the amount of information and data which are produced, are extremely massive. Hence, client will be confused with huge amount of data, and it is difficult to understand which ones are useful. Data mining can overcome this problem. While data mining is using on cloud computing, it is reducing time of processing, energy usage and costs. As the speed of ...
متن کاملApplication of non-linear regression and soft computing techniques for modeling process of pollutant adsorption from industrial wastewaters
The process of pollutant adsorption from industrial wastewaters is a multivariate problem. This process is affected by many factors including the contact time (T), pH, adsorbent weight (m), and solution concentration (ppm). The main target of this work is to model and evaluate the process of pollutant adsorption from industrial wastewaters using the non-linear multivariate regression and intell...
متن کامل