Bioprocess Optimization Based On Relevance Vector Regression Models and Evolutionary Programming Technique

This paper proposes a bioprocess optimization procedure based on Relevance Vector Regression models and evolutionary programming technique. Relevance Vector Regression scheme allows developing a compact and stable data-based process model avoiding time-consuming modeling expenses. The model building and process optimization procedure could be done in a half-automated way and repeated after every new cultivation run. The proposed technique was tested in a simulated mammalian cell cultivation process. The obtained results are promising and could be attractive for optimization of industrial bioprocesses.

ORPP with MAIEP Based Technique for Loadability Enhancement

One of the factors to maintain system survivability is the adequate reactive power support to the system. Lack of reactive power support may cause undesirable voltage decay leading to total system instability. Thus, appropriate reactive power support scheme should be arranged in order to maintain system stability. The strength of a system capacity is normally denoted as system loadability. This paper presents the enhancement of system loadability through optimal reactive power planning technique using a newly developed optimization technique, termed as Multiagent Immune Evolutionary Programming (MAIEP). The concept of MAIEP is developed based on the combination of Multiagent System (MAS), Artificial Immune System (AIS) and Evolutionary Programming (EP). In realizing the effectiveness of the proposed technique, validation is conducted on the IEEE-26-Bus Reliability Test System. The results obtained from pre-optimization and post-optimization process were compared which eventually revealed the merit of MAIEP.

An Efficient Technique for EMI Mitigation in Fluorescent Lamps using Frequency Modulation and Evolutionary Programming

Electromagnetic interference (EMI) is one of the serious problems in most electrical and electronic appliances including fluorescent lamps. The electronic ballast used to regulate the power flow through the lamp is the major cause for EMI. The interference is because of the high frequency switching operation of the ballast. Formerly, some EMI mitigation techniques were in practice, but they were not satisfactory because of the hardware complexity in the circuit design, increased parasitic components and power consumption and so on. The majority of the researchers have their spotlight only on EMI mitigation without considering the other constraints such as cost, effective operation of the equipment etc. In this paper, we propose a technique for EMI mitigation in fluorescent lamps by integrating Frequency Modulation and Evolutionary Programming. By the Frequency Modulation technique, the switching at a single central frequency is extended to a range of frequencies, and so, the power is distributed throughout the range of frequencies leading to EMI mitigation. But in order to meet the operating frequency of the ballast and the operating power of the fluorescent lamps, an optimal modulation index is necessary for Frequency Modulation. The optimal modulation index is determined using Evolutionary Programming. Thereby, the proposed technique mitigates the EMI to a satisfactory level without disturbing the operation of the fluorescent lamp.