A comparative study between scalarization approach and Pareto approach for multi-objective optimization problem using Genetic Algorithm (MOGA) formulated based on superconducting fault current limiter
Dey A.,IIEST |
1st IEEE International Conference on Power Electronics, Intelligent Control and Energy Systems, ICPEICES 2016 | Year: 2016
Optimal design of saturated iron-core superconducting fault current limiter (SISFCL) for satisfactory steady state and transient performance is very important. While designing the fault current limiter (FCL) utilizing Jiles-Atherton hysteresis model, it has been observed that a good fault current suppression ratio cannot be achieved without an appreciable voltage rise across the dc voltage source. Hence both objectives, suppressing the fault current and limiting the voltage rise across the dc voltage source are conflicting in nature and need to be optimized simultaneously. In this paper, two multi-objective optimization problem solving approach are compared. The first approach is scalarization whereas the second one is Pareto approach. A multi-objective GA algorithm for both the approaches is utilized to find the optimal solution for the satisfactory performance of SISFCL. © 2016 IEEE.
Patra S.,IIEST |
International Journal of Civil Engineering and Technology | Year: 2017
In the present paper a series of California Bearing Ratio (CBR) tests has been performed in both soaked and unsoaked condition on field samples collected from road subgrade. Four rural roads in West Bengal, India have been considered for collection of field CBR sample. From the experimental data it is found that with time the values of CBR in soaked and unsoaked condition increases irrespective of types of road subgrade. Based on the present experimental data a nonlinear power model has been developed to predict field soaked CBR value with time (CBRfst), in terms of field soaked CBR value at 0 days (CBRfs0) and time 't'. © IAEME Publication.
Bose A.,IIEST |
ACM International Conference Proceeding Series | Year: 2016
Recently compressed sensing or compressive sampling (CS), apart from its intrinsic applications of sub-sample signal reconstruction, is explored a lot in the design of bandwidth preserving-energy efficient wireless networks. At the same time, due to open nature of wireless channel, digital data (media) transmission needs their protection from unauthorized access and digital watermarking has been devised as one form of potential solution over the years. Among the various methods, spread spectrum (SS) watermarking is found to be efficient due to its improved robustness and imperceptibility. SS watermarking on digital images in presence of additive and multiplicative noise is studied a lot. To the best of knowledge, CS-SS watermarking in presence of both multiplicative (fading channel) and additive noise is not explored much in the existing literature. To address this problem, a wireless communication theoretic model is suggested here to develop an improved detection scheme on additive SS image watermark framework. System model considers sub-sample (CS) transmission of the watermarked image over both non-fading and fading channel. Then a diversity assisted weighted combining scheme for the improved water-mark detection is developed. An optimization problem is formulated where the weight for the individual link is calculated through eigen filter approach to maximize the water-mark detection probability for a fixed false alarm rate under the constraint of an embedding power (strength). A large set of simulation results validate the mathematical model of the diversity assisted compressive watermark detector. © 2016 ACM.
Sarkar B.K.,M.C.K.V.I.E |
2016 2nd International Conference on Control, Instrumentation, Energy and Communication, CIEC 2016 | Year: 2016
In the electricity pricing, the congestion management has become extremely important and it can impose unavoidable problems in electricity trading. In this paper, Gravitational Search Algorithm (GSA) based optimization is performed to address the optimal power flow (OPF) problem governed by contribution factor based ranking and nodal congestion price based ranking in order to achieve congestion relief and maximum economic benefit with desired voltage level and minimum system loss. The methodology has been tested on a typical IEEE test system. © 2016 IEEE.
Das S.,Hooghly Engineering and Technology College |
Advances in Intelligent Systems and Computing | Year: 2016
An offline signature verification system based on feature extraction from signature images is introduced. Varieties of features such as geometric features, topological features and statistical features are extracted from signature images using Gabor filter technique. As all the features are not relevant, only the salient features are selected from the extracted one by a Rough Set Theory based reduct generation technique. Thus only the relevant features of the signatures are retained to reduce the dimension of feature vector so as to reduce the computation time and are used for offline signature verification. The experimental results are expressed using few parameters such as False Rejection Rate (FRR), False Acceptance Rate (FAR). © Springer India 2016.
Ghosh H.,IIEST |
IEEE Sensors Journal | Year: 2016
Nanocrystalline silicon oxide impedance biosensor has a promising feature of displaying a concentration dependent resonant peak in the sensitivity characteristics which introduces an electrical marker for selectivity. However, the design of optimum pore geometry for a desirable combination of sensitivity, selectivity and repeatability is expected to be nontrivial due to the effect of electrical double layer impedance at the electrode-electrolyte interface and local charge modulation at the interface of the cylindrical and the hemispherical regions owing to the mutual interference of the electric field lines. In this paper, detailed theoretical and experimental investigations of the effect of pore geometry on the sensing performance have been reported. The pore impedance in the transmission line model of such sensors has been evaluated by solving the Poisson Nernst Planck equation using finite element method. Aflatoxin B1(AFB1) and Ochratoxin A(OTA) has been used as the specific and nonspecific antigen respectively. It has been observed that the sensitivity and selectivity parameters along with their repeatability index change oppositely and hence the maximum figure of merit does not vary in accordance with the aspect ratio of the pores. Further, the optimized dimensions have experimentally resulted in tripling of the figure of merit compared to the un-optimized dimension reported in previous literature. This effect has led to enhancement in accuracy of detection by more than an order of magnitude and selectivity by two orders of magnitude. © 2016 IEEE.
International Journal of Mechanical Sciences | Year: 2016
The present paper deals with the dynamical solution of a rectangular micropolar beam in high frequency domain. Analogous to symplectic approach by W. Zhong, a new methodology is adopted to solve the vibrational problem by using Hamiltonian principle with Legendre's transformation. This paper extends the symplectic elasticity approach and dual variables to a different version that simplifies the solution procedure. © 2016 Elsevier Ltd. All rights reserved.
De I.,MCKV Institute of Engineering |
Applied Soft Computing Journal | Year: 2015
Image quality assessment of distorted or decompressed images without any reference to the original image is challenging from computational point of view. Quality of an image is best judged by human observers without any reference image, and evaluated using subjective measures. The paper aims at designing a generic no-reference image quality assessment (NR-IQA) method by incorporating human visual perception in assigning quality class labels to the images. Using fuzzy logic approach, we consider information theoretic entropies of visually salient regions of images as features and assess quality of the images using linguistic values. The features are transformed into fuzzy feature space by designing an algorithm based on interval type-2 (IT2) fuzzy sets. The algorithm measures uncertainty present in the input-output feature space to predict image quality accurately as close to human observations. We have taken a set of training images belonging to five different pre-assigned quality class labels for calculating foot print of uncertainty (FOU) corresponding to each class. To assess the quality class label of the test images, maximum of T-conorm applied on the lower and upper membership functions of the test images belonging to different classes is calculated. Our proposed image quality metric is compared with other no-reference quality metrics demonstrating more accurate results and compatible with subjective mean opinion score metric. © 2015 Elsevier B.V. All rights reserved.
Mondal P.,IIEST |
Clean Technologies and Environmental Policy | Year: 2016
Techno-economic performance analysis of a biomass-fired combined cycle plant, employing a topping air turbine (AT) cycle and a bottoming steam turbine cycle, is reported in this paper. The net power output is 500 kWe, the AT producing 350 kWe and the ST producing the rest. Biomass (saw dust) is directly fired in a biomass combustor-heat exchanger (BCHX) duplex unit which supplies heat to the topping cycle. Influences of major plant parameters on the thermo-economic performance of the plant are analysed. Overall efficiency is found to maximise at topping cycle pressure ratio of 4. Higher TIT results in better energetic performance, while higher hot end temperature difference of the BCHX unit lowers the plant efficiency. Thermo-economic analysis reveals that the lowest unit cost of electricity (UCOE) of about 0.12 $/kWh could be achieved for the plant, while still giving an overall efficiency of about 48 %. Based on minimum UCOE, the payback period is estimated to be about 6 years with 50 % capital subsidy and about 13 years with no capital subsidy. © 2016 Springer-Verlag Berlin Heidelberg
Chattaraj S.,IIEST |
2016 IEEE 1st International Conference on Control, Measurement and Instrumentation, CMI 2016 | Year: 2016
High level of uncertainty present in the movement of an object in manoeuvering target tracking problem makes the system hard to model. Such a system is nonlinear as well due to the irregularity present in the availability of radar measurements. A conventional particle filter designed for this problem has the limitation of sample loss, which can be handled effectively by an evolutionary strategy based particle filter. Such filter can tackle complex nonlinear system such as the one just described, but its performance suffer for dealing with larger number of particles. Present work investigates one task scheduling scheme among processors, which helps in improving the estimation accuracy of one evolutionary particle filter by incorporating more measurements in its computation. © 2016 IEEE.