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

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

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.

Mortality rate in children caused by traffic accidents according to geographical regions : Brazil, 1997 - 2005

Lesões fatais em crianças causadas por acidentes de trânsito representam um problema em muitos países. Este estudo analisou a taxa de mortalidade em crianças passageiras de automóveis menores de 10 anos de idade no Brasil, entre 1997 e 2005. Para isso, o número de mortes foi obtido diretamente no banco de dados do Sistema de Informação sobre Mortalidade (SIM) e os dados da população são projeções intercensitárias a partir censo demográfico do Instituto Brasileiro de Geografia e Estatística (IBGE) disponíveis pelo site do DATASUS. Foram calculadas, para os triênios compreendidos no período em estudo, as taxas de mortalidade por acidente de trânsito entre crianças passageiras de automóveis segundo faixa etária (menor que 1 ano, 1 a 4 e 5 a 9) e região geográfica. Os resultados mostraram taxas de mortalidade de 5,68, 7,32 e 6,78 (por 1.000.000), respectivamente, para os períodos 1997-1999, 2000-2002 e 2003-2005 para todo o Brasil. Crianças menores de 1 ano de idade apresentam taxa de mortalidade de 10,18 (por 1,000,000), maior que as observadas para as outras faixas etárias. Para o período 1997-2005, as maiores taxas foram observadas nas regiões Centro-Oeste e Sul, representando, respectivamente, 13,88 e 11,47 (por 1.000.000). Tais resultados mostram a situação de risco da criança em relação a acidentes de trânsito como passageiras de automóveis e contribuem para a elaboração de campanhas educativas de prevenção de lesões.

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.

Tracing heme in a living cell: hemoglobin degradation and heme traffic in digest cells of the cattle tick Boophilus microplus

Heme is present in all cells, acting as a cofactor in essential metabolic pathways such as respiration and photosynthesis. Moreover, both heme and its degradation products, CO, iron and biliverdin, have been ascribed important signaling roles. However, limited knowledge is available on the intracellular pathways involved in the flux of heme between different cell compartments. The cattle tick Boophilus microplus ingests 100 times its own mass in blood. The digest cells of the midgut endocytose blood components and huge amounts of heme are released during hemoglobin digestion. Most of this heme is detoxified by accumulation into a specialized organelle, the hemosome.We followed the fate of hemoglobin and albumin in primary cultures of digest cells by incubation with hemoglobin and albumin labeled with rhodamine. Uptake of hemoglobin by digest cells was inhibited by unlabeled globin, suggesting the presence of receptor-mediated endocytosis. After endocytosis, hemoglobin was observed inside large digestive vesicles. Albumin was exclusively associated with a population of small acidic vesicles, and an excess of unlabeled albumin did not inhibit its uptake. The intracellular pathway of the heme moiety of hemoglobin was specifically monitored using Palladium-mesoporphyrin IX (Pd-mP) as a fluorescent heme analog. When pulse and chase experiments were performed using digest cells incubated with Pd-mP bound to globin (Pd-mP-globin), strong yellow fluorescence was found in large digestive vesicles 4 h after the pulse. By 8 h, the emission of Pd-mP was red-shifted and more evident in the cytoplasm, and at 12 h most of the fluorescence was concentrated inside the hemosomes and had turned green. After 48 h, the Pd-mP signal was exclusively found in hemosomes. In methanol, Pd-mP showed maximal emission at 550 nm, exhibiting a red-shift to 665 nm when bound to proteins in vitro.The red emission in the cytosol and at the boundary of hemosomes suggests the presence of heme-binding proteins, probably involved in transport of heme to the hemosome. The existence of an intracellular heme shuttle from the digestive vesicle to the hemosome acting as a detoxification mechanism should be regarded as a major adaptation of ticks to a blood-feeding way of life. To our knowledge, this is the first direct observation of intracellular transport of heme in a living eukaryotic cell. A similar approach, using Pd-mP fluorescence, could be applied to study heme intracellular metabolism in other cell types.

Urban Traffic Control and Monitoring - An Approach for the Brazilian Intelligent Cities Project

This paper describes an urban traffic control system which aims at contributing to a more efficient traffic management system in the cities of Brazil. It uses fuzzy sets, case-based reasoning, and genetic algorithms to handle dynamic and unpredictable traffic scenarios, as well as uncertain, incomplete, and inconsistent information. The system is composed by one supervisor and several controller agents, which cooperate with each other to improve the system's results through Artificial Intelligence Techniques.

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.

Fuzzy sets in distributed traffic control

The task of controlling urban traffic requires flexibility, adaptability and handling uncertain information spread through the intersection network. The use of fuzzy sets concepts convey these characteristics to improve system performance. This paper reviews a distributed traffic control system built upon a fuzzy distributed architecture previously developed by the authors. The emphasis of the paper is on the application of the system to control part of Campinas downtown area. Simulation experiments considering several traffic scenarios were performed to verify the capabilities of the system in controlling a set of coupled intersections. The performance of the proposed system is compared with conventional traffic control strategies under the same scenarios. The results obtained show that the distributed traffic control system outperforms conventional systems as far as average queues, average delay and maximum delay measures are concerned.

A fast electric load forecasting using neural networks

The objective of this work is the development of a methodology for electric load forecasting based on a neural network. Here, it is used Backpropagation algorithm with an adaptive process based on fuzzy logic. This methodology results in fast training, when compared to the conventional formulation of Backpropagation algorithm. Results are presented using data from a Brazilian Electric Company and the performance is very good for the proposal objective.

A fast electric load forecasting using adaptive neural networks

This work presents a procedure for electric load forecasting based on adaptive multilayer feedforward neural networks trained by the Backpropagation algorithm. The neural network architecture is formulated by two parameters, the scaling and translation of the postsynaptic functions at each node, and the use of the gradient-descendent method for the adjustment in an iterative way. Besides, the neural network also uses an adaptive process based on fuzzy logic to adjust the network training rate. This methodology provides an efficient modification of the neural network that results in faster convergence and more precise results, in comparison to the conventional formulation Backpropagation algorithm. The adapting of the training rate is effectuated using the information of the global error and global error variation. After finishing the training, the neural network is capable to forecast the electric load of 24 hours ahead. To illustrate the proposed methodology it is used data from a Brazilian Electric Company. © 2003 IEEE.

Method for estimating railroad track settlements due to dynamic traffic loads

This paper is the result of real-scale physical modeling study designed to simulate the load-deformation characteristics of railroad foundation systems that include the railroad ties, the ballast, and the sub-base layers of a railroad embankment. The study presents comparisons of the application of dynamic loads of 100kN on the rails, and the resulting deformations during a 500,000 cycle testing period for three rail support systems; wood, concrete and steel. The results show that the deformation curve has an exponential shape, with the larger portion of the deformation occurring during the first 50,000 load cycles followed by a tendency to stabilize between 100,000 to 500,000 cycles. These results indicate that the critical phase of deformations of a new railroad is within the first 50,000 cycles of loading, and after that, it slowly attenuates as it approaches a stable value. The paper also presents empirically derived formulations for the estimation of the deformations of the rail supports as a result of rail traffic.

Towards forecasting and mitigating ionospheric scintillation effects on GNSS

The effect of the ionosphere on the signals of Global Navigation Satellite Systems (GNSS), such as the Global Positionig System (GPS) and the proposed European Galileo, is dependent on the ionospheric electron density, given by its Total Electron Content (TEC). Ionospheric time-varying density irregularities may cause scintillations, which are fluctuations in phase and amplitude of the signals. Scintillations occur more often at equatorial and high latitudes. They can degrade navigation and positioning accuracy and may cause loss of signal tracking, disrupting safety-critical applications, such as marine navigation and civil aviation. This paper addresses the results of initial research carried out on two fronts that are relevant to GNSS users if they are to counter ionospheric scintillations, i.e. forecasting and mitigating their effects. On the forecasting front, the dynamics of scintillation occurrence were analysed during the severe ionospheric storm that took place on the evening of 30 October 2003, using data from a network of GPS Ionospheric Scintillation and TEC Monitor (GISTM) receivers set up in Northern Europe. Previous results [1] indicated that GPS scintillations in that region can originate from ionospheric plasma structures from the American sector. In this paper we describe experiments that enabled confirmation of those findings. On the mitigation front we used the variance of the output error of the GPS receiver DLL (Delay Locked Loop) to modify the least squares stochastic model applied by an ordinary receiver to compute position. This error was modelled according to [2], as a function of the S4 amplitude scintillation index measured by the GISTM receivers. An improvement of up to 21% in relative positioning accuracy was achieved with this technnique.

Spatial electric load forecasting using a local movement approach

An agent based model for spatial electric load forecasting using a local movement approach for the spatiotemporal allocation of the new loads in the service zone is presented. The density of electrical load for each of the major consumer classes in each sub-zone is used as the current state of the agents. The spatial growth is simulated with a walking agent who starts his path in one of the activity centers of the city and goes to the limits of the city following a radial path depending on the different load levels. A series of update rules are established to simulate the S growth behavior and the complementarity between classes. The results are presented in future load density maps. The tests in a real system from a mid-size city show a high rate of success when compared with other techniques. The most important features of this methodology are the need for few data and the simplicity of the algorithm, allowing for future scalability. © 2009 IEEE.