Monthly Average Forecasting of Wind Speed Using Time Series Models

Dokur E., Ceyhan S., Kurban M.,JECET; June 2017- August 2017; Sec. C; Vol.6. No.3, 260-269.,[DOI: 10.24214/jecet.C.6.3.26069]

Abstract

Wind speed modeling and prediction plays a critical role in wind related engineering studies. With the integration of wind energy into electricity grids, it is becoming increasingly important to obtain accurate wind speed forecasts. Accurate wind speed forecasts are necessary to schedule dispatch able generation and tariffs in the electricity market. The aim of this paper is to develop the most suitable models for monthly average forecasting of wind speeds using SARIMA (Seasonal Auto-Regressive Integrated Moving Average) models with some statistical tests. SARIMA models and statistical tests are implemented in MATLAB software. All the models are analyzed with real data of wind speeds collected over a period of 11 years, Bilecik, city of Turkey. Ljung-Box and Durbin Watson tests are carried out to ideal model. Accuracy of the forecasting is evaluated in terms of RMSE, MSE, and MAPE.

Gender Gap in Literacy

Deepamordia

Abstract

In this paper a statistical analysis of gender gap (district wise, statewisewise) of Rajasthan is given. A comparison between Gender gap of India and Rajasthan on the basis of area and the sex ratio is explained.

Footwear Industry in Bangladesh: Reduction of Lead time by using Lean Tools

Md. Abu Sayid Mia, Md. Nur-E-Alam, Md. Lutfor Rahman and M. Kamal Uddin; JECET; June 2017- August 2017; Sec. C; Vol.6. No.3, 251-259;[DOI: https://doi.org/10.24214/jecet.C.6.3.25159]

Abstract

The footwear industry is a booming and one of the largest manufacturing sectors in Bangladesh. This study was carried out in a leading footwear manufacturing industry in Bangladesh for the court shoe production line. The main target of this study was to reduce the lead time by using lean tools like Value Stream Mapping (VSM), Process Cycle Efficiency (PCE) and Pareto Analysis. Lean manufacturing is a systematic approach to identifying and eliminating wastes (non-value-added activities) through continuous improvement by conveying the product at the pull of the customer in pursuit of production. At present state, lead time, PCE and takt time of court shoe production were observed gradually 83867 sec, 8.32%, and 26.73 sec/pair. Ultimately, after the implementation of lean tools, at future state, the lead time, PCE and takt time of this production line 35866 sec, 19.46% and 15.26 sec/pair respectively.

Some Forms of Interpolation Formula Based on Divided Difference

Dhritikesh Chakrabarty, JECET; March 2017- May 2017; Sec. C; Vol.6. No.2, 199-211.,[DOI: https://doi.org/10.24214/jecet.C.6.2.19911]

Abstract

Some forms of interpolation formula have been searched for which can enable to represent a set of numerical data on a pair of variables by a polynomial curve. These have been derived from the interpolation formula, due to Newton, based on forward divided difference and from an interpolation formula, derived here, based on backward divided difference. Application of each of them to numerical data has also been shown in the case of data on total population of India and also of Assam.

Daily Solar Radiation Prediction Using Adaptive Fuzzy Rule Based Systems

Yılmaz S., Hocaoğlu F.O., Kurban M.,JECET; March 2017- May 2017; Sec. C; Vol.6. No.2, 184-198.,[DOI: https://doi.org/10.24214/jecet.C.6.2.18498]

Abstract

Daily solar radiation values are the most important parameters in renewable energy applications. However, these data are not always available and they cannot be obtained easily. The mean air temperature values are always available because they can be measured using a simple instrument. The prediction is very useful in solar energy applications because it permits to generate solar data for locations where measurements are not available. This paper proposes two fuzzy rule-based approaches for predicting of daily solar radiation data from only the air temperature and time durations. The first model has been designed using Adaptive Neuro-Fuzzy Inference System (ANFIS) and second model is a Mamdani fuzzy model that uses table look-up scheme. Common main advantage of these two approaches is that the rule-base of fuzzy systems is obtained from the previous data without expert knowledge. The results of two models have been compared and it has been seen that ANFIS model gives more reliable results.