In this paper, we address the problem of predicting the usage of home appliances where a key challenge is to model the everyday routine of homeowners and the inter-dependency between the use of different appliances. To this end, we propose an agent based prediction algorithm that captures the everyday habits by exploiting their periodic features. We demonstrate that our approach outperforms existing methods by up to 40% in experiments based on real-world data from a prominent database of home energy usage.

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Determining storage location and planning path are the two most important components in warehouse management. Simultaneous resolution of these problems not only reduces the storage and retrieval time but also avoids the loss of goods. The article offers a scenario of a practical cold warehouse system with narrow aisle racking, where space optimization and time schedules are always the top priority. There are two forklifts considered to work parallel in the system, so aisle dispute is considered to minimize safety risks in the warehouse. Two algorithms used to optimize the path were introduced in the paper, which is the closest open location – COL and A star algorithm. The COL helps to determine the most appropriate storage location according to the user's requirements, including the type of goods to be exported or imported, finding storage location of the nearest empty cell by referring the weight of the road and obstacle might happen by two forklift truck in the system. The result of this algorithm is the determined Input and Output point of each forklift path. The coordinate index ​​of these two points is returned as input to the A-star algorithm to determine the shortest path for the forklift. With the A star algorithm, a clear path will be sought, including the comparison of clashes between vehicles in the system, preferring the shortest path for moving between two points. The travel route results are exported for goods execution devices. The system is simulated by MATLAB combined with V-Rep software for an intuitive interface and fully illustrates each task of each vehicle from time to time. Some traditional or single algorithms with the same assumptions about the system were also simulated and compared to see the effectiveness of the combination of two COL and A star algorithms in a narrow aisle racking system.