A New Architecture Based on Artificial Neural Network and PSO Algorithm for Estimating Software Development Effort

Software project management has always faced challenges that have often had a great impact on the outcome of projects in future. For this, Managers of software projects always seek solutions against challenges. The implementation of unguaranteed approaches or mere personal experiences by managers does not necessarily suffice for solving the problems. Therefore, the management area of software projects requires tools and means helping software project managers confront with challenges. The estimation of effort required for software development is among such important challenges. In this study, a neural-network-based architecture has been proposed that makes use of PSO algorithm to increase its accuracy in estimating software development effort. The architecture suggested here has been tested by several datasets. Furthermore, similar experiments were done on the datasets using various widely used methods in estimating software development. The results showed the accuracy of the proposed model. The results of this research have applications for researchers of software engineering and data mining

A New Architecture Based on Artificial Neural Network and PSO Algorithm for Estimating Software Development Effort

Software project management has always faced challenges that have often had a great impact on the outcome of projects in future. For this, Managers of software projects always seek solutions against challenges. The implementation of unguaranteed approaches or mere personal experiences by managers does not necessarily suffice for solving the problems. Therefore, the management area of software projects requires tools and means helping software project managers confront with challenges. The estimation of effort required for software development is among such important challenges. In this study, a neural-network-based architecture has been proposed that makes use of PSO algorithm to increase its accuracy in estimating software development effort. The architecture suggested here has been tested by several datasets. Furthermore, similar experiments were done on the datasets using various widely used methods in estimating software development. The results showed the accuracy of the proposed model. The results of this research have applications for researchers of software engineering and data mining

The Impact of Information Technology on Service Quality, Satisfaction, and Customer Relationship Management (Case Study: IT Organization Individuals)

Recent research and studies have shown that Information Technology (IT) has a significant impact on service quality, customer satisfaction, and customer relationship development. With the proliferation and penetration of technology in all aspects of life, organizations are responding to the implications and opportunities that IT creates in relation to customer services. The main objective of using information technology in organizations is to increase customer satisfaction, service quality, and customer relationship management, which the authors will focus on here. Enhancing service quality, improving customer satisfaction, and establishing close and sustainable customer relationships are key advantages of leveraging information technology in this field. This article examines the impact of information technology on service quality, customer satisfaction, and customer relationship development and provides strategies and models for organizations to improve customer satisfaction and establish closer connections with them through the use of information technology. Seventy individuals from the IT field were used to evaluate the proposed model. The proposed model was compared with three models: SEM, regression, and decision tree, and the results demonstrated better performance of this approach

Software Effort Estimation: A Survey of Well-known Approaches

Project Failure is the glaring issue considering today while observed by software experts. The imprecision of the estimation is the reason for this challenge. Software effort estimation is the major fundamentals of software development. It truly is the liability of software project management; that he basically manages the financial plan challenges and also ought to handle the entire task within the assigned hour slot. Large amount of estimation techniques, models and also approaches are utilized; but yet not any of those can easily supply 100 % precision in cost, in time or else in any further estimation aspects. Precise estimation is a sophisticated procedure since it might be visualized like software effort forecast, since the phrase shows foresight not ever will become a reality. Effort estimation usually needs generalizing from a few old projects. Generalization from these kinds of restricted knowledge is an naturally under light situation. Variety of participants make their activities to generate different methods in last three decades. This article is related to the extensive descriptive discovery of the models which are introduced in the beginning of the software estimation area in addition to includes many of the well-known accessible and utilized parametric models or number of non-parametric methods. Furthermore evaluating the software estimation tactics detailed, and produces the choice of suitable estimation model simpler. The major summary is this not any unique approach is best for most circumstances, which an attentive assessment of the information on a number of methods might be to generate practical estimates

A Dataset-Independent Model for Estimating Software Development Effort Using Soft Computing Techniques

During the recent years, numerous endeavours have been made in the area of software development effort estimation for calculating the software costs in the preliminary development stages. These studies have resulted in the offering of a great many of the models. Despite the large deal of efforts, the substantial problems of the offered methods are their dependency on the used data collection and, sometimes, their lack of appropriate efficiency. The current article attempts to present a model for software development effort estimation through making use of evolutionary algorithms and neural networks. The distinctive characteristic of this model is its lack of dependency on the collection of data used as well as its high efficiency. To evaluate the proposed model, six different data collections have been used in the area of software effort estimation. The reason for the application of several data collections is related to the investigation of the model performance independence of the data collection used. The evaluation scales have been MMRE, MdMRE and PRED (0.25). The results have indicated that the proposed model, besides delivering high efficiency in contrast to its counterparts, produces the best responses for all of the used data collections