A novel neural model to electrical load forecasting in transformers

The paper describes a novel neural model to electrical load forecasting in transformers. The network acts as identifier of structural features to forecast process. So that output parameters can be estimated and generalized from an input parameter set. The model was trained and assessed through load data extracted from a Brazilian Electric Utility taking into account time, current, tension, active power in the three phases of the system. The results obtained in the simulations show that the developed technique can be used as an alternative tool to become more appropriate for planning of electric power systems.

Analysis of forecasting capabilities of ground surfaces valuation using artificial neural networks

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Electrical load forecasting formulation by a fast neural network

The objective of this work is to develop a methodology for electric load forecasting based on a neural network. Here, backpropagation algorithm is used with an adaptive process that based on fuzzy logic and using a decaying exponential function to avoid instability in the convergence process. This methodology results in fast training, when compared to the conventional formulation of backpropagation algorithm. The results are presented using data from a Brazilian Electric Company, and shows a very good performance for the proposal objective.

Electric load forecasting using a fuzzy ART&ARTMAP neural network

This work presents a neural network based on the ART architecture ( adaptive resonance theory), named fuzzy ART& ARTMAP neural network, applied to the electric load-forecasting problem. The neural networks based on the ARTarchitecture have two fundamental characteristics that are extremely important for the network performance ( stability and plasticity), which allow the implementation of continuous training. The fuzzy ART& ARTMAP neural network aims to reduce the imprecision of the forecasting results by a mechanism that separate the analog and binary data, processing them separately. Therefore, this represents a reduction on the processing time and improved quality of the results, when compared to the Back-Propagation neural network, and better to the classical forecasting techniques (ARIMA of Box and Jenkins methods). Finished the training, the fuzzy ART& ARTMAP neural network is capable to forecast electrical loads 24 h in advance. To validate the methodology, data from a Brazilian electric company is used. (C) 2004 Elsevier B.V. All rights reserved.

Multinodal Load Forecasting in Power Electric Systems using a Neural Network with Radial Basis Function

In this paper we present the results of the use of a methodology for multinodal load forecasting through an artificial neural network-type Multilayer Perceptron, making use of radial basis functions as activation function and the Backpropagation algorithm, as an algorithm to train the network. This methodology allows you to make the prediction at various points in power system, considering different types of consumers (residential, commercial, industrial) of the electric grid, is applied to the problem short-term electric load forecasting (24 hours ahead). We use a database (Centralised Dataset - CDS) provided by the Electricity Commission de New Zealand to this work.

Multi-Agent Simulation of Urban Social Dynamics for Spatial Load Forecasting

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

A Cellular Automaton Approach to Spatial Electric Load Forecasting

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Short-Term Multinodal Load Forecasting Using a Modified General Regression Neural Network

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Fear and adventure tourism in Brazil

The search for new non-routine emotions and sensations has become a decisive factor in taking part in adventure tourism. As Barros and Dines (2000) have pointed out, Brazil's natural resources are abundant and have been widely used to promote the nation's tourism. Empirical literature describes fear as one of the main emotions in adventure activities, and for this reason a questionnaire was designed to examine the presence of fear before and after three adventure activities (parachuting, white-water rafting, and rock-climbing). This study not only aimed to consolidate fear as a fundamental emotion in performing such activities but also to stimulate interest for further studies in this area. (C) 2009 Elsevier Ltd. All rights reserved.

Spatial electric load forecasting using an evolutionary heuristic

A method for spatial electric load forecasting using elements from evolutionary algorithms is presented. The method uses concepts from knowledge extraction algorithms and linguistic rules' representation to characterize the preferences for land use into a spatial database. The future land use preferences in undeveloped zones in the electrical utility service area are determined using an evolutionary heuristic, which considers a stochastic behavior by crossing over similar rules. The method considers development of new zones and also redevelopment of existing ones. The results are presented in future preference maps. The tests in a real system from a midsized city show a high rate of success when results are compared with information gathered from the utility planning department. The most important features of this method are the need for few data and the simplicity of the algorithm, allowing for future scalability.

Implementação de um sistema Collaborative Planning, Forecasting, and Replenishment em uma grande rede de fast food por meio de um prestador de serviços logísticos

A gestão colaborativa é, atualmente, um elemento-chave no contexto da gestão da cadeia de suprimentos. Neste artigo, o tema é abordado mediante a análise de um caso real, em que uma grande rede mundial de fast-food e seu prestador de serviço logístico (PSL) trabalharam conjuntamente no Brasil em um projeto-piloto para a implementação de um collaborative planning, forecasting, and replenishment (CPFR). O trabalho faz uso de uma metodologia de pesquisa-ação e apresenta as principais variáveis que influenciaram o projeto, abordando os processos necessários para a implementação e os pontos que favorecem o CPFR. Com base no caso estudado, o trabalho apresenta um conjunto de propostas sobre o papel dos agentes da cadeia em projetos dessa natureza. A gestão da cadeia de suprimentos por intermédio da coordenação direta de um PSL também permite demonstrar as possibilidades e dificuldades desse sistema, contribuindo com a visão colaborativa na cadeia de suprimentos a partir da relação entre seus agentes.

The use of simulation for forecasting the number of docks necessary in an expedition department

The simulation is a very powerful tool to develop more efficient systems, hence it is been widely used with the goal of productivity improvement. Its results, if compared with other methods, are not always optimum; however, if the experiment is rightly elaborated, its results will represent the real situation, enabling its use with a good level of reliability. This work used the simulation (through the ProModel (R) software) in order to study, understand, model and improve the expenditure system of an enterprise, with a premise of keeping the production-delivery flow considering quick, controlled and reliable conditions.

TOURISM IN CAVES and THE CONSERVATION of THE SPELEOLOGICAL HERITAGE: THE CASE of SERRA da BODOQUENA (MATO GROSSO do SUL STATE, BRAZIL)

Heros Augusto Santos Lobo & Edvaldo Cesar Moretti: Tourism in Caves and the Conservation of the Speleological Heritage: The case of Serra da Bodoquena (Mato Grosso do Sul State, Brazil)The Serra da Bodoquena is the region in the state of Mato Grosso do Sul, Brazil in which the Municipality of Bonito is located. This municipality is the primary calling card for tourism in the state and is one of the most developed areas of ecotourism and speleotourism in the country The tourism there is entitled ecotourism, and is designed to be sustainable. The present case study focuses on the ecologically Sustainable aspects of the spleotourism practiced there, especially the proposals for tourist carrying capacity adopted. The results and discussion provide Suggestions for the adoption of a different formulation of carrying capacity focusing on both operational and quantitative aspects. Ecologically Sustainable speleotourism in the Serra da Bodoquena should be possible as long as new proposals limiting visitation are adopted which conform to technical environmental management procedures and consider the interests of local stakeholders.

Multi-Agent Framework for Spatial Load Forecasting

A multi-agent framework for spatial electric load forecasting, especially suited to simulate the different dynamics involved on distribution systems, is presented. The service zone is divided into several sub-zones, each subzone is considered as an independent agent identified with a corresponding load level, and their relationships with the neighbor zones are represented as development probabilities. With this setting, different kind of agents can be developed to simulate the growth pattern of the loads in distribution systems. This paper presents two different kinds of agents to simulate different situations, presenting some promissory results.