oalib

OALib Journal期刊

ISSN: 2333-9721

费用：99美元

投稿

时间不限

( 2023 )

( 2022 )

( 2021 )

( 2020 )

自定义范围…

匹配条件： “Mrinal Kanti Ghose” ，找到相关结果约847条。
列表显示的所有文章，均可免费获取
第1页/共847条
每页显示 条
Comparing Soft Computing Techniques For Early Stage Software Development Effort Estimations
Roheet Bhatnagar,Mrinal Kanti Ghose
International Journal of Software Engineering & Applications , 2012,
Abstract: Accurately estimating the software size, cost, effort and schedule is probably the biggest challenge facing software developers today. It has major implications for the management of software development because both the overestimates and underestimates have direct impact for causing damage to software companies.Lot of models have been proposed over the years by various researchers for carrying out effort estimations. Also some of the studies for early stage effort estimations suggest the importance of early estimations. New paradigms offer alternatives to estimate the software development effort, in particular the Computational Intelligence (CI) that exploits mechanisms of interaction between humans and processes domain knowledge with the intention of building intelligent systems (IS). Among IS, Artificial Neural Network and Fuzzy Logic are the two most popular soft computing techniques for software development effort estimation. In this paper neural network models and Mamdani FIS model have been used to predictthe early stage effort estimations using the student dataset. It has been found that Mamdani FIS was able to predict the early stage efforts more efficiently in comparison to the neural network models based models.
Performance Analysis of AIM-K-means & K-means in Quality Cluster Generation
Samarjeet Borah,Mrinal Kanti Ghose
Computer Science , 2009,
Abstract: Among all the partition based clustering algorithms K-means is the most popular and well known method. It generally shows impressive results even in considerably large data sets. The computational complexity of K-means does not suffer from the size of the data set. The main disadvantage faced in performing this clustering is that the selection of initial means. If the user does not have adequate knowledge about the data set, it may lead to erroneous results. The algorithm Automatic Initialization of Means (AIM), which is an extension to K-means, has been proposed to overcome the problem of initial mean generation. In this paper an attempt has been made to compare the performance of the algorithms through implementation
Comparing Soft Computing Techniques For Early Stage Software Development Effort Estimations
Roheet Bhatnagar,Mrinal Kanti Ghose
Computer Science , 2012,
Abstract: Accurately estimating the software size, cost, effort and schedule is probably the biggest challenge facing software developers today. It has major implications for the management of software development because both the overestimates and underestimates have direct impact for causing damage to software companies. Lot of models have been proposed over the years by various researchers for carrying out effort estimations. Also some of the studies for early stage effort estimations suggest the importance of early estimations. New paradigms offer alternatives to estimate the software development effort, in particular the Computational Intelligence (CI) that exploits mechanisms of interaction between humans and processes domain knowledge with the intention of building intelligent systems (IS). Among IS, Artificial Neural Network and Fuzzy Logic are the two most popular soft computing techniques for software development effort estimation. In this paper neural network models and Mamdani FIS model have been used to predict the early stage effort estimations using the student dataset. It has been found that Mamdani FIS was able to predict the early stage efforts more efficiently in comparison to the neural network models based models.
Software Development Effort Estimation – Neural Network Vs. Regression Modeling Approach
Roheet Bhatnagar,Vandana Bhattacharjee,Mrinal Kanti Ghose
International Journal of Engineering Science and Technology , 2010,
Abstract: The global software development industry has now become more matured and complex. The industry is making use of newer tools and approaches of software development. The challenge then lies in accurately modeling and predicting the software development effort, and then create project development schedule. This work employs a neural network (NN) approach and a multiple regression modeling approach to model and predict the software development effort based on an available real life dataset which is prepared by Lopez-Martin et al. [1, 2]. A comparison between results obtained by both the approaches is presented. It is concluded that NN is able to successfully model the complex, non-linear relationship between a large number of effort drivers and the software maintenance effort, with results closely matching the effort estimated by experts.
EFFICIENT TECHNIQUE FOR AUTOMATIC EXTRACTION AND IDENTIFICATION OF ELEVATION FROM A REFERENCE IMAGE
Mohan Pratap Pradhan,Mrinal Kanti Ghose,Gourav Mittal
International Journal of Computers & Technology , 2013,
Abstract: In Geographic information system (GIS) identification of elevation detail pertaining to a contour in a reference map or topological map plays an important role while creating digital elevation model or digital surface model of a terrain. Traditional technique involving manual identification of elevation demands greater effort and time where in one needs to tediously identify and enter the elevation value. These identified elevations can be later used for creating digital elevation model. In order to reduce the complexity involved in same, effective and efficient automated technique can be devised that identifies the elevation associated with a contour. In addition the automated technique should also ensure correctness and reliability of the elevation details identified. The alignment of elevation details in the feature space adds to the complexity of the problem. Over years several techniques have been proposed based on object oriented technique and pattern detection. This proposed work introduces a novel rotation invariant technique for identifying number associated with contours taking into consideration friend pattern chain of the significant pixels representing a digit in a number.
Splice Loss of Graded-Index Fibers: Accurate Semianalytical Descriptions Using Nelder-Mead Nonlinear Unconstrained Optimization with Three-Parameter Fundamental Modal Field
Raja Roy Choudhury,Arundhati Roy Choudhury,Mrinal Kanti Ghose
Advances in Optical Technologies , 2013, DOI: 10.1155/2013/168923
Abstract: A faster and accurate semianalytical formulation with a robust optimization solution for estimating the splice loss of graded-index fibers has been proposed. The semianalytical optimization of modal parameters has been carried out by Nelder-Mead method of nonlinear unconstrained minimization suitable for functions which are uncertain, noisy, or even discontinuous. Instead of normally used Gaussian function, as the trial field for the fundamental mode of graded-index optical fiber a novel sinc function with exponentially and ( is the normalized radius of the optical fiber) decaying trailing edge has been used. Due to inclusion of three parameters in the optimization of fundamental modal solution and application of an efficient optimization technique with simple analytical expressions for various modal parameters, the results are found to be accurate and computationally easier to find than the standard numerical method solution. 1. Introduction Single mode fiber is considered as the most important broadband transmission media for optical communication system. Achieving accurate values of modal field distribution in such fiber is very essential, as it can provide basic solutions for wave equation and many useful properties like splice loss, microbending loss, fiber coupling, and the prediction of intramodal dispersion [1]. However, the various expressions for the fundamental modal field that have been reported so far are not able to predict propagation constant and modal parameters exactly in all regions of single mode operation [2]. The Gaussian approximation shows poor accuracy for lower normalized frequency region although this region may involve single mode fiber operation [2]; however, it can perform satisfactorily only for higher normalized frequency region and give good result near the cut-off frequency of next higher mode [3]. Besides, it is also equally important that the approximation should describe the field in the cladding accurately, as it is useful in the study of evanescent coupling problem. To overcome these inefficiencies, an exponentially and decaying trailing edge fundamental modal field solution in core-cladding interface region has been considered. To achieve higher accuracy compared to Gaussian function, the Gaussian-Hankel [2], the generalized Gaussian [4], the extended Gaussian [5], and the Laguerre-Gauss/Bessel expansion approximation [6, 7] have been proposed so far. An approximate analytical description with no requirement for optimization has also been presented [8]. But such analytical expression may not work for all
A note on complex L1-predual spaces
Mrinal Kanti Das
International Journal of Mathematics and Mathematical Sciences , 1990, DOI: 10.1155/s0161171290000564
Abstract: Some characterizations of complex L1-predual spaces are proved.
On complex L1-predual spaces
Mrinal Kanti Das
International Journal of Mathematics and Mathematical Sciences , 1987, DOI: 10.1155/s0161171287000073
Abstract: This paper contains some characterisations of complex L-balls, including interpolation theorems which are analogs of Edward's separation theorem for simplices.
Quantization dimension for Gibbs-like measures on cookie-cutter sets
Mrinal Kanti Roychowdhury
Mathematics , 2012,
Abstract: In this paper using Banach limit we have determined a Gibbs-like measure $\mu_h$ supported by a cookie-cutter set $E$ which is generated by a single cookie-cutter mapping $f$. For such a measure $\mu_h$ and a given $r\in (0, +\infty)$ we have determined the quantization dimension function $D_r:=D_r(\mu_h)$, and established its functional relationship with the temperature function of the thermodynamic formalism. The temperature function is commonly used to perform the multifractal analysis, in our context of the measure $\mu_h$.
Quantization and centroidal Voronoi tessellations for probability measures on dyadic Cantor sets
Mrinal Kanti Roychowdhury
Mathematics , 2015,
Abstract: In this paper, we investigate the optimal sets of $n$-means and the centroidal Voronoi tessellations with $n$ generators for a Borel probability measure $P$ on $\mathbb R$ supported by a dyadic Cantor set generated by two self-similar mappings with similarity ratios $r$ where $0.4364590141\leq r\leq 0.4512271429$.
第1页/共847条
每页显示 条


Home
Copyright © 2008-2020 Open Access Library. All rights reserved.