The data mining(1) standard process divides a data mining project into six phases, i.e. business understanding, data understanding, data preparation, modeling, evaluation and deployment. The goal of the data understan...
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ISBN:
(纸本)9781450365123
The data mining(1) standard process divides a data mining project into six phases, i.e. business understanding, data understanding, data preparation, modeling, evaluation and deployment. The goal of the data understanding phase is to understand the original data. At present, there are relatively few studies on this phase. In practical applications, some visualization methods are usually used to understand the original data. Therefore, we propose a systematic process for data understanding, and make full use of visualization technology to help users understand the data. In addition, we revise the dp (Density Peaks) algorithm to identify the high-density region, and integrate it into the data understanding process. The experimental results show that the data understanding process proposed in this paper is effective.
In this paper, we discuss a method of a textual transformation between the similar languages taking Mongolian as an example. The textual transformation approach is performed by combining a knowledge-based rule bank wi...
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In this paper, we discuss a method of a textual transformation between the similar languages taking Mongolian as an example. The textual transformation approach is performed by combining a knowledge-based rule bank with data driven method. dp algorithm(dynamic programming) is applied to matching of the source and target language words. Our experimental results demonstrate that the proposed method has achieved 83.9% transformation accuracy(in F-measure) from NM(Cyrillic) to TM(Traditional Mongolian) text, and 88.1% for NM to TODO.
We present a real-time optimization framework to manage Hybrid Residential Electrical Systems (HRES) with multiple Energy sources and heterogeneous storage units. HRES represents urban buildings where photovoltaic (PV...
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ISBN:
(纸本)9783981537024
We present a real-time optimization framework to manage Hybrid Residential Electrical Systems (HRES) with multiple Energy sources and heterogeneous storage units. HRES represents urban buildings where photovoltaic (PV) or other renewable sources are installed along with the traditional connection to the main grid. In this paper heterogeneous storage units are used to realize energy buffers for the exceeding energy produced by the renewable when buildings and the grid are not available to accept it. We considered two different battery banks as electric energy storage, in particular lead-acid as the primary one for its low price and low self-discharge rate;while the lithium-ion chemistry is used as secondary bank because of the higher energy density and higher number of cycles. The proposed optimization strategy aims at maximizing the lifetime of the battery banks and to reduce the energy bill by managing the variability of the PV source, in price-varying scenarios. We used a Dynamic-Programming (dp) algorithm to schedule off-line the use of the lead-acid bank minimizing the number of cycles and the Depth-of-Discharge (DoD) under given irradiance forecasts and user load profiles. Forecasts of the user loads and of the renewable energy intake are introduced in the optimization. Moreover a Real-Time scheme is introduced to manage the lithium bank and to minimize the need and the purchase of energy from the Grid when the actual demand does not fit the forecast. Our simulation results outperform the state of the art where the efficiency of both banks is not taken into consideration, even if complex approaches based on dp are used.
This paper researched multi-stage inventory system and established limited inventory Markov model, on the other hand it induced dp algorithm of limited inventory Markov model. The results proved that the reorder point...
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This paper researched multi-stage inventory system and established limited inventory Markov model, on the other hand it induced dp algorithm of limited inventory Markov model. The results proved that the reorder point of multi-stage inventory system can guarantee demand, and also allows the storage costs to a minimum level in accordance with the above model.
This paper researched multi-stage inventory system and established limited inventory Markov model and its dp *** results proved that the reorder point of multistage inventory system can guarantee demand,and also allow...
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This paper researched multi-stage inventory system and established limited inventory Markov model and its dp *** results proved that the reorder point of multistage inventory system can guarantee demand,and also allows the storage costs to a minimum level in accordance with the above model.
Many combinatorial problems can be efficiently solved for partial k-trees (graphs of treewidth bounded by k). The edge-coloring problem is one of the well-known combinatorial problems for which no NC algorithms have b...
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Many combinatorial problems can be efficiently solved for partial k-trees (graphs of treewidth bounded by k). The edge-coloring problem is one of the well-known combinatorial problems for which no NC algorithms have been obtained for partial k-trees. This paper gives an optimal and first NC parallel algorithm to find an edge-coloring of any given partial k-tree with bounded degrees using a minimum number of colors. In the paper k is assumed to be bounded.
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