947 resultados para Electric networks - Planning


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Artificial neural network (ANN) learning methods provide a robust and non-linear approach to approximating the target function for many classification, regression and clustering problems. ANNs have demonstrated good predictive performance in a wide variety of practical problems. However, there are strong arguments as to why ANNs are not sufficient for the general representation of knowledge. The arguments are the poor comprehensibility of the learned ANN, and the inability to represent explanation structures. The overall objective of this thesis is to address these issues by: (1) explanation of the decision process in ANNs in the form of symbolic rules (predicate rules with variables); and (2) provision of explanatory capability by mapping the general conceptual knowledge that is learned by the neural networks into a knowledge base to be used in a rule-based reasoning system. A multi-stage methodology GYAN is developed and evaluated for the task of extracting knowledge from the trained ANNs. The extracted knowledge is represented in the form of restricted first-order logic rules, and subsequently allows user interaction by interfacing with a knowledge based reasoner. The performance of GYAN is demonstrated using a number of real world and artificial data sets. The empirical results demonstrate that: (1) an equivalent symbolic interpretation is derived describing the overall behaviour of the ANN with high accuracy and fidelity, and (2) a concise explanation is given (in terms of rules, facts and predicates activated in a reasoning episode) as to why a particular instance is being classified into a certain category.

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This paper presents a model for estimation of average travel time and its variability on signalized urban networks using cumulative plots. The plots are generated based on the availability of data: a) case-D, for detector data only; b) case-DS, for detector data and signal timings; and c) case-DSS, for detector data, signal timings and saturation flow rate. The performance of the model for different degrees of saturation and different detector detection intervals is consistent for case-DSS and case-DS whereas, for case-D the performance is inconsistent. The sensitivity analysis of the model for case-D indicates that it is sensitive to detection interval and signal timings within the interval. When detection interval is integral multiple of signal cycle then it has low accuracy and low reliability. Whereas, for detection interval around 1.5 times signal cycle both accuracy and reliability are high.

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This paper discusses the areawide Dynamic ROad traffic NoisE (DRONE) simulator, and its implementation as a tool for noise abatement policy evaluation. DRONE involves integrating a road traffic noise estimation model with a traffic simulator to estimate road traffic noise in urban networks. An integrated traffic simulation-noise estimation model provides an interface for direct input of traffic flow properties from simulation model to noise estimation model that in turn estimates the noise on a spatial and temporal scale. The output from DRONE is linked with a geographical information system for visual representation of noise levels in the form of noise contour maps.

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Voltage Unbalance (VU) is a power quality issue arising within the low voltage residential distribution networks due to the random location and rating of single-phase rooftop photovoltaic cells (PVs). In this paper, an analysis has been carried out to investigate how PV installations, their random location and power generation capacity can cause an increase in VU. Several efficient practical methods are discussed for VU reduction. Based on this analysis, it has been shown that the installation of a DSTATCOM can reduce VU. In this paper, the best possible location for DSTATCOM and its efficient control method to reduce VU will be presented. The results are verified through PSCAD/EMTDC and Monte Carlo simulations.

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The overarching aim of this study is to create new knowledge about how playful interactions (re)create the city via ubiquitous technologies, with an outlook to apply the knowledge for pragmatic innovations in relevant fields such as urban planning and technology development in the future. The study looks at the case of transyouth, the in-between demographic bridging youth and adulthood in Seoul, one of the most connected, densely populated, and quickly transforming metropolises in the world. To unravel the elusiveness of ‘play’ as a subject and the complexity of urban networks, this study takes a three-tier transdisciplinary approach comprised of an extensive literature review, Shared Visual Ethnography (SVE), and interviews with leading industry representatives who design and develop the playscape for Seoul transyouth. Through these methodological tools, the study responds to the following four research aims: 1. Examine the sociocultural, technological, and architectural context of Seoul 2. Investigate Seoul transyouth’s perception of the self and their technosocial environment 3. Identify the pattern of their playful interaction through which meanings of the self and the city are recreated 4. Develop an analytical framework for enactment of play This thesis argues that the city is a contested space that continuously changes through multiple interactions among its constituents on the seam of control and freedom. At the core of this interactive (re)creation process is play. Play is a phenomenon that is enacted at the centre of three inter-related elements of pressure, possibility, and pleasure, the analytical framework this thesis puts forward as a conceptual apparatus for studying play across disciplines. The thesis concludes by illustrating possible trajectories for pragmatic application of the framework for envisioning and building the creative, sustainable, and seductive city.