• Shazia Manzoor
• Zahid Hussain Wani

Software cost estimation predicts the amount of effort and development time required to build any software system. There are a number of cost estimation models. Each of these models have their own pros and cons in estimating the development cost and effort. Recently, the usage of Meta-heuristic techniques for software cost estimations is increasingly growing. Prerequisite of relative accurate estimation is work experience. Therefore, the risk associated with construction of software projects is based on preliminary estimates. Increasing risk causes increasing uncertainty about the initial program with increasing complexity and size of projects level of uncertainty become higher. So in this paper, we propose an approach, which consists of Functional Link ANN and Harmony search algorithm as its training algorithm. FLANN reduces the computational complexity in multilayer neural network. It does not have any hidden layer, and has got the fast learning ability. In our work, MRE, MMRE and MdMRE were selected as the performance index to gauge the quality of prediction of the proposed model. Extensive evaluation of results show that training a FLANN with harmony search algorithm for the Software Cost prediction problem gives out highly improved set of results. In addition the proposed model is structurally simple and requires less computation during training as the model contains no hidden layer.

Artificial Neural Network (ANN), Harmony Search, Functional Link Artificial Neural Network(FLANN), Software Cost Estimation(SCE).

"A Hybrid of Harmony Search and Functional Link Artificial Neural Network Model for Software Cost Estimation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.5, Issue 8, page no.573-580, August-2018, Available :http://www.jetir.org/papers/JETIR1808984.pdf

"A Hybrid of Harmony Search and Functional Link Artificial Neural Network Model for Software Cost Estimation", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.5, Issue 8, page no. pp573-580, August-2018, Available at : http://www.jetir.org/papers/JETIR1808984.pdf