By successfully solving the problem of forecasting, the processes in the work of various companies are optimized and savings are achieved. In this process, the analysis of time series data is of particular importance. Since the creation of Facebook’s Prophet, and Amazon’s DeepAR+ and CNN-QR forecasting models, algorithms have attracted a great deal of attention. The paper presents the application and comparison of the above algorithms for sales forecasting in distribution companies. A detailed comparison of the performance of algorithms over real data with different lengths of sales history was made. The results show that Prophet gives better results for items with a longer history and frequent sales, while Amazon’s algorithms show superiority for items without a long history and items that are rarely sold.

This paper presents a framework capable of accurately forecasting future sales in the retail industry and classifying the product portfolio according to the expected level of forecasting reliability. The proposed framework, that would be of great use for any company operating in the retail industry, is based on Facebook's Prophet algorithm and backtesting strategy. Real-world sales forecasting benchmark data obtained experimentally in a production environment in one of the biggest retail companies in Bosnia and Herzegovina is used to evaluate the framework and demonstrate its capabilities in a real-world use case scenario.

Considering that most faults in overhead power lines are transient, fast and reliable algorithms for determining types of faults are needed. Reliable algorithm allows design of adaptive system for improving service continuity by automatically restoring power to the line after a momentary fault. This paper describes the procedure for real-time adjustment of algorithm for detection of arc faults in overhead power lines. This adjustment refers to real-time implementation of algorithm on DSP microcontroller. Given the nature of the problem and strict requirements for testing algorithm in real experiment, procedure for testing hardware in simulation loop is developed. Hardware in the loop (HIL) technique is based on MATLAB/Simulink, NI CB-68LP data acquisition card and simplified simulation model of faults in overhead power lines.