Multiscale Forecasting Models Based on Singular Values for Nonstationary Time Series

Time series are valuable sources of information for supporting planning activities. Transport, fishery, economy and finances are predominant sectors concerned into obtaining information in advance to improve their productivity and efficiency. During the last decades diverse linear and nonlinear forecasting models have been developed for attending this demand. However the achievement of accuracy follows being a challenge due to the high variability of the most observed phenomena. In this research are proposed two decomposition methods based on Singular Value Decomposition of a Hankel matrix (HSVD) in order to extract components of low and high frequency from a nonstationary time series. The proposed decomposition is used to improve the accuracy of linear and nonlinear autoregressive models. The evaluation of the proposed forecasters is performed through data coming from transport sector and fishery sector. Series of injured persons in traffic accidents of Santiago and Valparaíso and stock of sardine and anchovy of central-south Chilean coast are used. Further, for comparison purposes, it is evaluated the forecast accuracy reached by two decomposition techniques conventionally used, Singular Spectrum Analysis (SSA) and decomposition based on Stationary Wavelet Transform (SWT), both joint with linear and nonlinear autoregressive models. The experiments shown that the proposed methods based on Singular Value Decomposition of a Hankel matrix in conjunction with linear or nonlinear models reach the best accuracy for one-step and multi-step ahead forecasting of the studied time series.Sociedad Argentina de Informática e Investigación Operativa (SADIO

Unsteady blood flow with nanoparticles through stenosed arteries in the presence of periodic body acceleration

The effects of nanoparticles such as Fe304,Ti02, and Cu on blood flow inside a stenosed artery are studied. In this study, blood was modelled as non-Newtonian Bingham plastic fluid subjected to periodic body acceleration and slip velocity. The flow governing equations were solved analytically by using the perturbation method. By using the numerical approaches, the physiological parameters were analyzed, and the blood flow velocity distributions were generated graphically and discussed. From the flow results, the flow speed increases as slip velocity increases and decreases as the values of yield stress increases

Modeling CPUE series for the fishery along northeast coast of India: A comparison between the Holt- Winters, ARIMA and NNAR models

Mathematical as well as statistical models not only help in understanding the dynamics of fish populations but also enables in short-term predictions on abundance. In the present study, three univariate forecasting techniques viz., Holt-Winters, Autoregressive Integrated Moving Average and Neural Network Autoregression were used to model the CPUE data series along northeast coast of India. Quarterly landings data which spans from January 1985 to December 2014 was used for building the model and forecasting. The accuracy of the forecast was measured using Mean Absolute Error, Root Mean Square Error and Mean Absolute Percent Error. Based on the comparison of the model, performance of Holt-Winter’s model was found to provide more accurate forecasts than the Autoregressive Integrated Moving Average and Neural Network Autoregression model. A Holt-Winters model with smoothing factors α = 0.172, β = 0, γ = 0.529 was found as the suitable model. The presence of seasonality in the series is evident from gamma value. An ARIMA model with one non-seasonal moving average term combined with two seasonal moving average terms was found to be suitable to model the CPUE series based on the Akaike Information Criteria. Among the Neural Network Autoregression models used to fit the CPUE series, a configuration of 13 lagged inputs and one hidden layer with 7 neurons provided the best fit

PICES Press, Vol. 8, No. 1, January 2000

The state of PICES science - 1999 The status of the Bering Sea: January - July, 1999 The state of the western North Pacific in the second half of 1998 The state of the eastern North Pacific since February 1999 MEQ/WG 8 Practical Workshop Michael M. Mullin - A biography Highlights of Eighth Annual Meeting Mechanism causing the variability of the Japanese sardine population: Achievements of the Bio-Cosmos Project in Japan Climate change, global warming, and the PICES mandate – The need for improved monitoring The new age of China-GLOBEC study GLOBEC activities in Korean waters Aspects of the Global Ocean Observing System (GOOS

Book of Abstracts

ICES Annual Science Conference, 19 – 23 September 2011, Gdańsk Music and Congress Center, Gdańsk, Poland. IMR contributors: Benjamin Planque, Torild Johansen, Tuula Skarstein, Jon‐Ivar Westgaard, Halvor Knutsen, Kristin Helle, Michael Pennington, Marek Ostrowski, Nils Olav Handegard, Mette Skern‐Mauritzen, Edda Johannesen, Ulf Lindstrøm, Harald Gjøsæter, Ken Drinkwater, Trond Kristiansen, Geir Ottersen, Esben Moland Olse

Impacts of climate change on fisheries and aquaculture

The 2015 Paris Climate Agreement recognizes the need for effective and progressive responses to the urgent threat of climate change, through mitigation and adaptation measures, while taking into account the particular vulnerabilities of food production systems. The inclusion of adaptation measures in the fisheries and aquaculture sector is currently hampered by a widespread lack of targeted analyses of the sector's vulnerabilities to climate change and associated risks, as well as the opportunities and responses available. This report provides the most up-to-date information on the disaggregated impacts of climate change for marine and inland fisheries, and aquaculture, in the context of poverty alleviation and the differential dependency of countries on fish and fishery resources. The work is based on model projections, data analyses, as well as national, regional and basin-scale expert assessments. The results indicate that climate change will lead to significant changes in the availability and trade of fish products, with potentially important geopolitical and economic consequences, especially for those countries most dependent on the sector