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Abstract. Nowadays, business intelligence (BI) has the top-most priority for the contemporary enterprises. The aim of this paper is to emphasize the advantages of this computer based approach in improving business processes. Data analytics and modeling of sales prediction system for enterprise is realized with artificial neural networks (ANNs). For the purpose of this research are created over 100 artificial neural networks. Three types of artificial neural networks are designed and evaluated: Function fitting neural networks, Focused Time-delay neural networks and NARX (Non-linear autoregressive) neural networks. Also were performed simulations with different architectures that differ to the number of delays and the number of neurons in the hidden layer. The network prediction performance was evaluated with Average Percentage Error (APE) and Root Mean Square Error (RMSE). The obtained results show big accuracy in prediction of the product sale. The precise prediction has influence to optimization of most of the business processes such as: supply of raw materials, organization of production process, staff scheduling, plan the electricity demand, cost reduction etc.

Computer-assisted analysis in biogeography is becoming one of the major research topics in the physical geography. Interestingly, the bioinformatics software tools provide good models for better understanding of a biological process. We have utilized them in finding the relationship between Ohrid lake endemic species of Salmo Letnica and other eight fishes from the Salmonidae family that constitute three subfamilies. The study of phylogenetics with considerable research interest in the phylogenetic relationships among the endemic fish species of Ohrid Lake is the main focus of this research article. Salmonidae family is found to be a big family constituting three subfamilies including Salmoninae family. The main research of the present work is aimed at the fishes from the Salmoninae family with more focus on the Salmo genus. Eight types of fishes from the mentioned genus were used in the process of creation of two different phylogenetic trees namely Neighbor-Joining and Unweighted Pair Group Method with Arithmetic Mean (UPGMA) phylogenetic tree. In order to create the trees, the accessions codes for the mitochondrial DNA sequences adopted from the National Center for Biotechnology Information website were imported into MATLAB for further analysis. The resulting trees were investigated further to understand clearly the correlation of Salmo Letnica with the other eight fishes.

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