JMASM 55: MATLAB Algorithms and Source Codes of \u27cbnet\u27 Function for Univariate Time Series Modeling with Neural Networks (MATLAB)

Artificial Neural Networks (ANN) can be designed as a nonparametric tool for time series modeling. MATLAB serves as a powerful environment for ANN modeling. Although Neural Network Time Series Tool (ntstool) is useful for modeling time series, more detailed functions could be more useful in order to get more detailed and comprehensive analysis results. For these purposes, cbnet function with properties such as input lag generator, step-ahead forecaster, trial-error based network selection strategy, alternative network selection with various performance measure and global repetition feature to obtain more alternative network has been developed, and MATLAB algorithms and source codes has been introduced. A detailed comparison with the ntstool is carried out, showing that the cbnet function covers the shortcomings of ntstool

Forecasting TRY/USD Exchange Rate with Various Artificial Neural Network Models

Exchange rate forecasting is one of the most common subjects among the forecasting problem field. Researchers and academicians from many different disciplines proposed various approaches for better exchange rate forecasting. In recent years, for solving the stated forecasting problem artificial neural networks have become successful tool to obtain solutions. Many different artificial neural networks have been used, developed and still developing for even better and trustable forecasts. In this study, TRY/USD exchange rate forecasting is modeled with different learning algorithms, activations functions and performance measures. Various Artificial Neural Network (ANN) models for better forecasting were investigated, compared and the obtained forecasting results interpreted respectively. The results of the application show that Variable Learning Rate Backpropagation learning algorithm with tan-sigmoid activation function has the best performance for TRY/USD exchange rate forecasting

Efficacy of entecavir treatment among chronic hepatitis B nucleos(t)ide-naive and -experienced patients

WOS: 000347840000016PubMed: 25790537Background/aim: To evaluate the efficacy of entecavir (ETV) among chronic hepatitis B (CHB) nucleos(t) ide-naive and -experienced patients in clinical practice. Materials and methods: In this retrospective study 85 CHB patients who had been receiving ETV and who attended our clinic since 2007 were included. Fifty patients were nucleos(t) ide analogue (NA)-naive. Factors including sex, positive HBeAg, baseline HBV DNA level, baseline alanine aminotransferase level, and prior lamivudine (LAM) resistance were evaluated in terms of their predictive role in treatment response, which was defined as a serum HBV DNA decrease of < 31.4 copies/mL. Results: Resistance was detected in 18 (51.4%) of 35 lamivudine-experienced patients. Virological response (VR) was achieved in 48 (96.0%) of NA-naive patients, while 16 (45.7%) of NA-experienced patients achieved VR. LAM-resistant patients had significantly lower response rates (P < 0.001). More responders with a low initial viral load achieved VR at the end of the 12-month follow-up period compared to those with a high initial viral load (91.7% vs. 70.0%, P = 0.004). Conclusion: ETV has greater efficacy in NA-naive patients and in NA-experienced patients without prior LAM resistance. The rate of VR achievement at 12 months was higher in patients who initially had a low viral load with ETV treatment

Late Pleistocene to Holocene paleoenvironmental evolution of Lake Hazar, Eastern Anatolia, Turkey

High-resolution seismic reflection profiles and core analyses in Lake Hazar provide a detailed record of the lake level fluctuations and the robust chronology of paleoclimatic events of the Eastern Anatolia during the late Pleistocene to Holocene. The earlier period of Marine Isotope Stage 3 (MIS-3) prior to 48 cal ka BP was accompanied by considerable lake level drop below 95 m, whereas the lake level increase during the later period (ca. 48-29 cal ka BP) gave rise to deposition of a transgressive unit with typical of aggradational architecture in the seismic reflection profiles. High climate variability with the Greenland interstadials and stadials (Dansgard-Oeschger and Heinrich events) in Lake Hazar are sensitively recorded in the core sediments by using multi-proxy analyses. Adjustment of seismic units correlating with the radiocarbon-dated chronostratigraphic units in the studied cores implies that the early Marine Isotope Stage 2 (MIS-2) is marked by an another lowstand lake level existed at ca. -90 m during 29-23 cal ka BP. In comparision to MIS-3 stage, the multi-proxy analyses reveal a general dry evaporative condition during most of the Last Glacial Maximum. In Lake Hazar, the maximum humidity in the late glacial period existed during 14.9-13.5 cal ka BP. The existence of a hiatus in the sedimentary record is documented in the seismic data that coincides with the cold and dry Younger Dryas period, implying a remarkable lake level drop. The multi-proxy records of the Holocene sediments reveal that a maximum precipitation in the early Holocene period prevailed during 10.1-9.3 cal ka BP, leading water level rise in the lake. In Lake Hazar, the middle Holocene until 4.9 cal ka BP is represented by highly climate variations, indicating a series of shorter wet and longer dry climate periods. The late Holocene is accompanied by lake level rises under a general wet climate condition that was interrupted by short dry climate intervals during 3.7-3.3 cal ka BP, 2.8-2.6 cal ka BP and 2.1-1.8 cal ka BP. (C) 2017 Elsevier Ltd and INQUA. All rights reserved