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The article presents the solution of information computer technology for creating an information-administrative database on operation of housing stock and the optimized strategy of administrative decisions directed to effective functioning of the enterprises of housing and communal services. It describes the method of a comparative assessment of efficiency of functioning of the enterprises of housing...
Consumption of electrical and electronic equipment (WEEE) is rapidly increasing in developing countries. Usually, there are no available data about amounts of WEEE generated in these countries. The assessment of present and future amounts of obsolete devices is a crucial step for the establishment of efficient waste collection and treatment systems.
In this paper a new approach to construction the short-term forecasting systems of river floods is introduced. It provides highly accurate forecasting results due to operative obtaining and integrated processing the remote sensing and ground-based water flow data in real time. Forecasting of floods areas and depths is performed on a time interval of 6 to 48 hours to be able to take the necessary steps...
The paper suggests a method for analyzing technology trends. The process, which investigates development of technologies over time, identifies main technologies displaying the fastest growth compared to greater influence of new inventions. The method analyzes term frequency and change over time of technological terms in academic articles and patents to identify the prior technologies that lead to...
This paper represents the second part of an entire study which focuses on multi-time series and -time scale modeling in wind speed and wind power forecasting. In the first part of the entire study [1], firstly, moving average (MA), weighted moving average (WMA), autoregressive moving average (ARMA) and autoregressive integrated moving average (ARIMA) models are introduced in-depth. Afterwards, the...
In this paper we characterize the frequency response of net stock amplification when the Damped Trend forecasting is used in the Order-Up-To replenishment policy. We prove that the invertibility regions from forecasting perspective are identical to the stability regions in control theory. From these stable and invertible regions, we explore the desirable parameter regions that the forecasting and...
Electrical energy consumption is affected by many parameters. These includes the variables related to power system itself, weather and climatic factors and socio-economic being of the energy consumers. In this paper, two components of load forecasting are classified. The parameters that influence the energy consumption and the methods used to forecast the energy consumption are reviewed. It is observed...
In the planning process of a supply chain, demand forecast have an important role in planning process of a company. The forecasts have to be as accurate as possible in order to allow the optimization of production, avoiding extra stocking costs or lost sales. In the case of spare parts, the challenge arises as the demand presents intermittent behavior. Nowadays, many forecast techniques, namely ARIMA...
Photovoltaic (PV) solar power capacity is growing in several countries, either concentrated in medium/large size solar parks or distributed by the medium and low voltage grid. Solar power forecasting is a key input for supporting grid management, participation in the electricity market and maintenance planning. This paper proposes a new forecasting system that is a hybrid of different models, such...
Numerous Fuzzy Time Series (FTS) models have been proposed in scientific literature during the past decades or so. Among the most FTS models for forecasting we chose two applicable models, Markov-Chain and Percentage Chang models. For evaluating these models we used exchange rate between the Iran and US dollar and compared the result.
The development of modern services cannot do without the staffs in this field. As the global industry transfers from industrial economy to service economy, the labor demand for modern services keeps increasing. The research reviews labor demand theories and its various incidence impacts, and carries out forecast research and incidence research of the number of people engaged in services in the future...
Cooperative hunting is a challenging and critical issue in multi-AUV system research. To conduct the cooperative hunting by multi-AUV in underwater environments, the AUVs not only need to take into account catch the target efficiently, but also need to avoid path conflict. In this paper, a novel algorithm based on bio-inspired neural network is proposed for the cooperative hunting by multi-AUV. Firstly,...
This research explores the dynamic relation between price, temperature and humidity; and its effect on electricity consumption of electric appliances. It develops prediction models for electricity consumption based on these variables. It is important that reliable methods are employed in modelling and prediction of energy needs otherwise inappropriate models and poor forecasts may occur. In this research,...
Time series data analyze and prediction is very important to the study of nonlinear phenomenon. Studies of time series prediction have a long history since last century, linear models such as autoregressive integrated moving average (ARIMA) model, and nonlinear models such as multi-layer perceptron (MLP) are well-known. As the state-of-art method, a deep belief net (DBN) using multiple Restricted...
Integrating wind power into the grid is challenging because of its random nature. Integration is facilitated with accurate short-term forecasts of wind power. The paper presents a spatio-temporal wind speed forecasting algorithm that incorporates the time series data of a target station and data of surrounding stations. Inspired by Compressive Sensing (CS) and structured-sparse recovery algorithms,...
Accurate solar power forecasting allows utilities to get the most out of the solar resources on their systems. To truly measure the improvements that any new solar forecasting methods can provide, it is important to first develop (or determine) baseline and target solar forecasting at different spatial and temporal scales. This paper aims to develop baseline and target values for solar forecasting...
This paper presents a novel detrending algorithm that allows long-term natural gas demand signals to be used effectively to generate high quality short-term natural gas demand forecasting models. Short data sets in natural gas forecasting inadequately represent the range of consumption patterns necessary for accurate short-term forecasting. In contrast, longer data sets present a wide range of customer...
Wind power forecasting is one of the most important aspects for power system with integration of wind power. In this work, Component GARCH-M (CGARCH-M) model is presented for short-term wind power forecasting (STWPF). Moreover, asymmetric and distributional considerations are taken into account to generalize the CGARCH-M type models. The CGARCH-M type models can decompose the volatility structure...
The worldwide increase in the integration of photovoltaic generation has necessitated improvements in the forecasting approaches. Two models are proposed to cater for PV generation forecasts for few minutes to several hours look-ahead times. A very fast and accurate prediction model based on extreme learning machine is deployed for day-ahead prediction. Moreover, an adaptive and sequential model is...
The paper proposes a hybrid architecture for electricity price forecasting. The proposed architecture combines the advantages of the easy-to-use and relatively easy-to-tune Autoregressive Integrated Moving Average (ARIMA) models and the approximation power of local learning techniques. The architecture is robust and more accurate than the individual forecasting methodologies on which it is based,...
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