Modelagem Fuzzy para previsão de uma série temporal de energia elétrica.

Esta dissertação testa e compara dois tipos de modelagem para previsão de uma mesma série temporal. Foi observada uma série temporal de distribuição de energia elétrica e, como estudo de caso, optou-se pela região metropolitana do Estado da Bahia. Foram testadas as combinações de três variáveis exógenas em cada modelo: a quantidade de clientes ligados na rede de distribuição de energia elétrica, a temperatura ambiente e a precipitação de chuvas. O modelo linear de previsão de séries temporais utilizado foi um SARIMAX. A modelagem de inteligência computacional utilizada para a previsão da série temporal foi um sistema de Inferência Fuzzy. Na busca de um melhor desempenho, foram feitos testes de quais variáveis exógenas melhor influenciam no comportamento da energia distribuída em cada modelo. Segundo a avaliação dos testes, o sistema Fuzzy de previsão foi o que obteve o menor erro. Porém dentre os menores erros, os resultados dos testes também indicaram diferentes variáveis exógenas para cada modelo de previsão.

Tecnologia da Informação no Controle Gerencial: um estudo de caso na estruturação de um modelo de metas de indicadores de desempenho da Empresa Alfa

A presente pesquisa objetiva verificar a contribuição da tecnologia da informação na previsão de indicadores de desempenho da Empresa Alfa. Para a realização deste estudo, foi realizado um estudo de caso único a fim de aprofundar na pesquisa de forma exploratória e descritiva. As técnicas utilizadas para tal foram análise documental e entrevista, que deram suporte à pesquisa quantitativa atendendo ao objetivo proposto no estudo e na fundamentação teórica. A pesquisa teve como base principal os resultados dos indicadores de desempenho dos anos de 2012 e 2013 descritos no planejamento estratégico referente ao ano de 2013. Através desses resultados foi possível prever os resultados dos indicadores para 2014 utilizando o software Weka e assim realizar as análises necessárias. Os principais achados demonstram que a Empresa Alfa precisará antecipar ações para maximizar seus resultados evitando que impactem negativamente na rentabilidade, além de ter a necessidade de manter uma base de dados sólida e estruturada que possa subsidiar previsões confiáveis e alimentar futuramente o programa a fim de realizar novas previsões. O resultado da pesquisa aponta que o sistema de informações Weka contribui para a previsão de resultados, podendo antecipar ações para que a organização possa otimizar suas tomadas de decisões, tornando-as mais eficientes e eficazes.

PICES Press, Vol. 18, No. 2, Summer 2010

•The 2010 Inter-sessional Science Board Meeting: A Note from the Science Board Chairman (pp. 1-3) •2010 Symposium on “Effects of Climate Change on Fish and Fisheries” (pp. 4-11) •2009 Mechanism of North Pacific Low Frequency Variability Workshop (pp. 12-14) •The Fourth China-Japan-Korea GLOBEC/IMBER Symposium (pp. 15-17, 23) •2010 Sendai Ocean Acidification Workshop (pp. 18-19, 31) •2010 Sendai Coupled Climate-to-Fish-to-Fishers Models Workshop (pp. 20-21) •2010 Sendai Salmon Workshop on Climate Change (pp. 22-23) •2010 Sendai Zooplankton Workshop (pp. 24-25, 28) •2010 Sendai Workshop on “Networking across Global Marine Hotspots” (pp. 26-28) •The Ocean, Salmon, Ecology and Forecasting in 2010 (pp. 29, 44) •The State of the Northeast Pacific during the Winter of 2009/2010 (pp. 30-31) •The State of the Western North Pacific in the Second Half of 2009 (pp. 32-33) •The Bering Sea: Current Status and Recent Events (pp. 34-35, 39) •PICES Seafood Safety Project: Guatemala Training Program (pp. 36-39) •The Pacific Ocean Boundary Ecosystem and Climate Study (POBEX) (pp. 40-43) •PICES Calendar (p. 44)

Filtragem adaptativa aplicada à redução de desvios em séries temporais de previsão numérica climática.

Esta dissertação apresenta resultados da aplicação de filtros adaptativos, utilizando os algoritmos NLMS (Normalized Least Mean Square) e RLS (Recursive Least Square), para a redução de desvios em previsões climáticas. As discrepâncias existentes entre o estado real da atmosfera e o previsto por um modelo numérico tendem a aumentar ao longo do período de integração. O modelo atmosférico Eta é utilizado operacionalmente para previsão numérica no CPTEC/INPE e como outros modelos atmosféricos, apresenta imprecisão nas previsões climáticas. Existem pesquisas que visam introduzir melhorias no modelo atmosférico Eta e outras que avaliam as previsões e identificam os erros do modelo para que seus produtos sejam utilizados de forma adequada. Dessa forma, neste trabalho pretende-se filtrar os dados provenientes do modelo Eta e ajustá-los, de modo a minimizar os erros entre os resultados fornecidos pelo modelo Eta e as reanálises do NCEP. Assim, empregamos técnicas de processamento digital de sinais e imagens com o intuito de reduzir os erros das previsões climáticas do modelo Eta. Os filtros adaptativos nesta dissertação ajustarão as séries ao longo do tempo de previsão. Para treinar os filtros foram utilizadas técnicas de agrupamento de regiões, como por exemplo o algoritmo de clusterização k-means, de modo a selecionar séries climáticas que apresentem comportamentos semelhantes entre si. As variáveis climáticas estudadas são o vento meridional e a altura geopotencial na região coberta pelo modelo de previsão atmosférica Eta com resolução de 40 km, a um nível de pressão de 250 hPa. Por fim, os resultados obtidos mostram que o filtro com 4 coeficientes, adaptado pelo algoritmo RLS em conjunto com o critério de seleção de regiões por meio do algoritmo k-means apresenta o melhor desempenho ao reduzir o erro médio e a dispersão do erro, tanto para a variável vento meridional quanto para a variável altura geopotencial.

A habilidade preditiva e os impactos dos choques na política monetária e no câmbio: comparações entre modelos DSGE, VAR e BVAR estimados para o Brasil

Este artigo compara a habilidade preditiva foradaamostra de um modelo DSGE (DynamicStochastic General EquilibriumModel)Novo-Keynesiano, especificado e estimado para o Brasil, com a de um modelo Autorregressivo Vetorial (VAR) e com a de um modelo AutorregressivoVetorial Bayesiano (BVAR). O artigo inova em relação a outros trabalhos similares feitos para o Brasil (Castro et al. (2011) e Caetano e Moura (2013)), ao escolher uma especificação para o modelo DSGE que, ao permitir o uso de um conjunto de informação mais rico, tornou possível computar-se a habilidade preditiva do DSGE a partir de previsões que são,verdadeiramente,previsõesfora da amostra. Ademais, diferentemente de outros artigos que utilizaram dados brasileiros, avalia-se em que medida as respostas das variáveis aos choques na política monetária e no câmbio, obtidas pelo modelo DSGE, se assemelham àquelas de um BVAR estimado através de procedimentos bayesianos desenvolvidos de forma consistente. O modelo DSGE estimado é similar ao utilizado por Justiniano e Preston (2010) e Alpanda (2010). O modelo BVAR foi estimado utilizando uma metodologia semelhante à desenvolvida por Sims e Zha (1998), Waggoner e Zha (2003) e Ramírez, Waggoner e Zha (2007).Os resultados obtidos mostram que o modelo DSGE é capaz de gerar, para algumas variáveis, previsões competitivas em relação às dos outros modelos rivais VAR e BVAR. Além disso, as respostas das variáveis aos choques nas políticas monetária e cambial, nos modelos DSGE e BVAR, são bastante similares.

Seascape ecology of coastal biogenic habitats: advances, gaps, and challenges

We review the progress made in the emerging field of coastal seascape ecology, i.e. the application of landscape ecology concepts and techniques to the coastal marine environment. Since the early 1990s, the landscape ecology approach has been applied in several coastal subtidal and intertidal biogenic habitats across a range of spatial scales. Emerging evidence indicates that animals in these seascapes respond to the structure of patches and patch mosaics in different ways and at different spatial scales, yet we still know very little about the ecological significance of these relationships and the consequences of change in seascape patterning for ecosystem functioning and overall biodiversity. Ecological interactions that occur within patches and among different types of patches (or seascapes) are likely to be critically important in maintaining primary and secondary production, trophic transfer, biodiversity, coastal protection, and supporting a wealth of ecosystem goods and services. We review faunal responses to patch and seascape structure, including effects of fragmentation on 5 focal habitats: seagrass meadows, salt marshes, coral reefs, mangrove forests, and oyster reefs. Extrapolating and generalizing spatial relationships between ecological patterns and processes across scales remains a significant challenge, and we show that there are major gaps in our understanding of these relationships. Filling these gaps will be crucial for managing and responding to an inevitably changing coastal environment. We show that critical ecological thresholds exist in the structural patterning of biogenic ecosystems that, when exceeded, cause abrupt shifts in the distribution and abundance of organisms. A better understanding of faunal–seascape relationships, including the identifications of threshold effects, is urgently needed to support the development of more effective and holistic management actions in restoration, site prioritization, and forecasting the impacts of environmental change.

Integration of data for nowcasting of harmful algal blooms

Harmful algal blooms (HABs) are a significant and potentially expanding problem around the world. Resource management and public health protection require sufficient information to reduce the impacts of HABs by response strategies and through warnings and advisories. To be effective, these programs can best be served by an integration of improved detection methods with both evolving monitoring systems and new communications capabilities. Data sets are typically collected from a variety of sources, these can be considered as several types: point data, such as water samples; transects, such as from shipboard continuous sampling; and synoptic, such as from satellite imagery. Generation of a field of the HAB distribution requires all of these sampling approaches. This means that the data sets need to be interpreted and analyzed with each other to create the field or distribution of the HAB. The HAB field is also a necessary input into models that forecast blooms. Several systems have developed strategies that demonstrate these approaches. These range from data sets collected at key sites, such as swimming beaches, to automated collection systems, to integration of interpreted satellite data. Improved data collection, particularly in speed and cost, will be one of the advances of the next few years. Methods to improve creation of the HAB field from the variety of data types will be necessary for routine nowcasting and forecasting of HABs.

Predicting the distribution of Vibrio vulnificus in Chesapeake Bay

Vibrio vulnificus is a gram-negative pathogenic bacterium endemic to coastal waters worldwide, and a leading cause of seafood related mortality. Because of human health concerns, understanding the ecology of the species and potentially predicting its distribution is of great importance. We evaluated and applied a previously published qPCR assay to water samples (n = 235) collected from the main-stem of the Chesapeake Bay (2007 – 2008) by Maryland and Virginia State water quality monitoring programs. Results confirmed strong relationships between the likelihood of Vibrio vulnificus presence and both temperature and salinity that were used to develop a logistic regression model. The habitat model demonstrated a high degree of concordance (93%), and robustness as subsequent bootstrapping (n=1000) did not change model output (P > 0.05). We forced this empirical habitat model with temperature and salinity predictions generated by a regional hydrodynamic modeling system to demonstrate its utility in future pathogen forecasting efforts in the Chesapeake Bay.

Wave forecasts associated with hurricane landfalls in the vicinity of Cape Lookout, North Carolina

Hurricanes can cause extensive damage to the coastline and coastal communities due to wind-generated waves and storm surge. While extensive modeling efforts have been conducted regarding storm surge, there is far less information about the effects of waves on these communities and ecosystems as storms make landfall. This report describes a preliminary use of NCCOS’ WEMo (Wave Exposure Model; Fonseca and Malhotra 2010) to compute the wind wave exposure within an area of approximately 25 miles radius from Beaufort, North Carolina for estuarine waters encompassing Bogue Sound, Back Sound and Core Sound during three hurricane landfall scenarios. The wind wave heights and energy of a site was a computation based on wind speed, direction, fetch and local bathymetry. We used our local area (Beaufort, North Carolina) as a test bed for this product because it is frequently impacted by hurricanes and we had confidence in the bathymetry data. Our test bed conditions were based on two recent Hurricanes that strongly affected this area. First, we used hurricane Isabel which made landfall near Beaufort in September 2003. Two hurricane simulations were run first by passing hurricane Isabel along its actual path (east of Beaufort) and second by passing the same storm to the west of Beaufort to show the potential effect of the reversed wind field. We then simulated impacts by a hurricane (Ophelia) with a different landfall track, which occurred in September of 2005. The simulations produced a geographic description of wave heights revealing the changing wind and wave exposure of the region as a consequence of landfall location and storm intensity. This highly conservative simulation (water levels were that of low tide) revealed that many inhabited and developed shorelines would receive wind waves for prolonged periods of time at heights far above that found during even the top few percent of non-hurricane events. The simulations also provided a sense for how rapidly conditions could transition from moderate to highly threatening; wave heights were shown to far exceed normal conditions often long before the main body of the storm arrived and importantly, at many locations that could impede and endanger late-fleeing vessels seeking safe harbor. When joined with other factors, such as storm surge and event duration, we anticipate that the WEMo forecasting tool will have significant use by local emergency agencies and the public to anticipate the relative exposure of their property arising as a function of storm location and may also be used by resource managers to examine the effects of storms in a quantitative fashion on local living marine resources.

1988 summer drought over the Great Plains: some causes and predictions

EXTRACT (SEE PDF FOR FULL ABSTRACT): The 1988 summer drought over much of the United States is described in terms of hemispheric mid-tropospheric flow patterns, temperature and precipitation anomalies, and sea surface temperature patterns. This drought was similar to earlier Great Plains droughts, although spatially more extensive than most. Three attempts to predict this drought from antecedent spring were moderately successful, though no one anticipated its severity and extent. ... A modified barotropic model iterating from a mean summer estimate of seasonal forcing from the May mid-tropospheric height pattern was reasonably successful in forecasting the drought. Sea surface temperature indications show that cold water (La Niña) along the equator subsequent to the 1987 El Niño, while contributory, cannot be considered a principal cause of the drought, since earlier cold water episodes did not produce drought, and other drought episodes occurred in the absence of cold equatorial waters.

Skill of monthly forecasts during the Northern Hemisphere summer

We have performed GCM experiments using the National Meteorological Center's Medium Range Forecasting (MRF) model to study the skill of monthly forecasts during the Northern Hemisphere summer and to test the impact of sea surface temperature anomalies (SSTAs) on such forecasts. The daily skill varies a great deal. The skillful daily forecasts last from 5 to 8 days for the Southern Hemisphere and from 6 to 8 days for the Northern Hemisphere. SSTAs have positive impact on the forecasts in the tropics and surface variables, but the impact of tropical SSTAs on the extra-tropical circulation is, in general, positive but small. Overall, the initial conditions play a more important role than SSTAs in determining the forecast skill.

Status of the shore area from Tiengiang to Camau: causes of accumulation and erosion

The paper presents some results of the research programs which had been performed during 1996-1999 (“Studying of river-sea interaction in the mouth of Tien river” and KHCN.06.08). Based on these results the morphological schemes of the shore areas from Tiengiang to Camau were compiled; causes and mechanics of accumulation and erosion were also determined. These results may be used as scientific basis for forecasting the development of the shoreline, it will contribute to the management, protection and reasonable exploitation the shore areas.

Preliminary studies on predicting the setting season of oysters for the benefit of shellfish farmers

Preliminary findings from a spatfall forecasting programme initiated in April 1981 at Himamaylan River, Negros Occidental are presented. Two main activities are involved: 1) monitoring of daily counts of oyster larvae in the plankton; and 2) monitoring of actual setting of oysters on standardized collectors put in the vicinity of oyster farm sites. Findings indicate that when the count of mature larvae exceeds 5 per 100 ml sample and persists for at least 3 days, spat may be expected to occur shortly afterwards.

Water budgeting studies on the hatchery and nursery rearing practices for the common carp, Cyprinus carpio (Linnaeus, 1758)

Aquaculture systems are an integral element of rural development and therefore should be environment friendly as well as socially and economically designed. From the economic standpoint, one of the major constraints for the development of sustainable aquaculture includes externalities generated by competition in access to a limited resource. This study was conducted as an investigation into the water requirement for the hatchery and nursery production phases of common carp, Cyprinus carpio (Linnaeus, 1758) at the Maharashtra State Fish Seed Farm at Khopoli in Raigad Dist. of Maharashtra during the winter months from November to February. The water budgeting study involves the quantification of water used in every stage of production in hatchery and nursery systems and aimed at becoming a foundation for the minimization of water during production without affecting the yield; thereby conserving water and upholding the theme of sustainable aquaculture. The total water used in a single operation cycle was estimated to be 11,25,040 L [sic]. Out of the total water consumed, 4.74% water was used in the pre-operational management steps, 4.48% was consumed during breeding, 62.72% was consumed in the hatching phase, 21.50% was used for hatchery rearing and 6.56% was consumed during conditioning. In the nursery ponds, the water gain was primarily the regulated inflow coming through the irrigation channel. The total quantum of water used in the nursery rearing was 31,60,800 L [sic]. The initial filling and regulated inflow formed 42.60% and 57.40% respectively of water gain, while evaporation, seepage and discharge contributed 20.71%, 36.46% and 42.82% respectively to the water loss. The total water expended for the entire operation was 1,21,61,120 L [sic]. Water expense occurred to produce a single spawn in the hatchery system was calculated and found to be 0.56 L while the water expended to produce one fry was calculated as 4.86 L. The study fulfills the hydrological equation described by Winter (1981) and Boyd (1985). It also validates the water budget simulation model that can be used for forecasting water requirements for aquaculture ponds (Nath and Bolte, 1998).