Proper Forecasting Research Articles

Time Series Forecasting Using a Two-Level Multi-Objective Genetic Algorithm: A Case Study of Maintenance Cost Data for Tunnel Fans

The aim of this study has been to develop a novel two-level multi-objective genetic algorithm (GA) to optimize time series forecasting data for fans used in road tunnels by the Swedish Transport Administration (Trafikverket). Level 1 is for the process of forecasting time series cost data, while level 2 evaluates the forecasting. Level 1 implements either a multi-objective GA based on the ARIMA model or a multi-objective GA based on the dynamic regression model. Level 2 utilises a multi-objective GA based on different forecasting error rates to identify a proper forecasting. Our method is compared with using the ARIMA model only. The results show the drawbacks of time series forecasting using only the ARIMA model. In addition, the results of the two-level model show the drawbacks of forecasting using a multi-objective GA based on the dynamic regression model. A multi-objective GA based on the ARIMA model produces better forecasting results. In level 2, five forecasting accuracy functions help in selecting the best forecasting. Selecting a proper methodology for forecasting is based on the averages of the forecasted data, the historical data, the actual data and the polynomial trends. The forecasted data can be used for life cycle cost (LCC) analysis.

Abrupt Intensification and Dissipation of Tropical Cyclones in Indian Ocean: A Case Study of Tropical Cyclone Nilofar – 2014

This study aims to investigate the possible influence of different atmospheric forcing on intensification/dissipation of tropical cyclonic “Nilofar” in Arabian Sea appeared during the last week of October, 2014 which exhibited abrupt intensification and dissipation as well. The cyclone was monitored by the Tropical Cyclone Warning Center (TCWC) of Pakistan Meteorological | department and the Regional Specialized Meteorological Center (RSMC) of Indian Meteorological | department (IMD) continuously, issued warnings and advisories with the help of available synoptic observations, satellite data and numerical models. Almost all the essential ingredients for intensification and tracking of the cyclone were studied and monitored accurately. Although the track forecast of the cyclone remained up to mark; but great errors occurred in intensity forecast. The atmospheric vertical wind shear could not be studied accurately. The intensity of wind shear itself is dependent on both; the local and global atmospheric forcing and climate variables, reoccurring periodically, especially while occurring two or more at the same time. More studies are required for influence of these climate variables while co-occurring at the same time period. This study will help weather forecasters to pay special attention on variation of climate factors affecting the wind shear for proper forecasting of tropical cyclones in the Arabian Sea for the safety of coastal communities along the coast.

SPATIO-TEMPORAL CHANGE MODELING OF LULC: A SEMANTIC KRIGING APPROACH

Abstract. Spatio-temporal land-use/ land-cover (LULC) change modeling is important to forecast the future LULC distribution, which may facilitate natural resource management, urban planning, etc. The spatio-temporal change in LULC trend often exhibits non-linear behavior, due to various dynamic factors, such as, human intervention (e.g., urbanization), environmental factors, etc. Hence, proper forecasting of LULC distribution should involve the study and trend modeling of historical data. Existing literatures have reported that the meteorological attributes (e.g., NDVI, LST, MSI), are semantically related to the terrain. Being influenced by the terrestrial dynamics, the temporal changes of these attributes depend on the LULC properties. Hence, incorporating meteorological knowledge into the temporal prediction process may help in developing an accurate forecasting model. This work attempts to study the change in inter-annual LULC pattern and the distribution of different meteorological attributes of a region in Kolkata (a metropolitan city in India) during the years 2000-2010 and forecast the future spread of LULC using semantic kriging (SemK) approach. A new variant of time-series SemK is proposed, namely Rev-SemKts to capture the multivariate semantic associations between different attributes. From empirical analysis, it may be observed that the augmentation of semantic knowledge in spatio-temporal modeling of meteorological attributes facilitate more precise forecasting of LULC pattern.

Supply Chain Management: A Case of Foodworld, Bangalore

One of the major challenges of Supply Chain Management is co-ordination of processes among different organisations that are part of supply chain. Managing inventory in different stages and at the same time providing cost effective services to the customer is of utmost importance. Supply chain management is a complex network of different organizations who are involved in fulfilling service/product requirement of customer. This exploratory study is about FoodWorld: pioneer in retail sector in India. The objective of the case is to discuss supply chain practices of FoodWorld and their challenges. As it is difficult to judge boundary of Supply Chain management (SCM), so proper forecasting is a tough exercise. Cooper et al. (1997), argues that, “research is needed to define and expand the boundaries of supply chain management.” Smart and efficient supply chain is able to gain Supply Chain Surplus, which is one of the key objectives. The process of managing the inventory at FoodWorld is through perpetual inventory and demand forecasting. These processes are based on historical data and managing the inventory and manpower. ERP at FoodWorld is managing efficient flow of information all across its front and back office. The SCM at FoodWorld is a blend of use of technology as well as classical technique.

Intérêt d’une approche téléradiographique basée sur les entités trigéminales dans l’étude de la morphologie sagittale de sujets sénégalais

The aim of this study was to determine the morphological characteristics of a Senegalese population based on an original cephalometric analysis using landmarks corresponding to the bony entrance or emergence of sensory fibers of the trigeminal nerve. One hundred and five lateral cephalograms of Senegalese patients were assessed in a cross sectional study. The landmarks used were based on cranial foramina i.e. ovale (TO), rotundum (TGR), supraorbital (ESO), infraorbital (TSO), incisive (CPA), lesser palatine (CPP), mandibular (IM) and mental (TM). Seven angular measurements were determined on each cephalogram. t test was used to assess differences in cephalometric variable between subjects grouped according to sex (male and female) and age bracket (< 12 years and > or = 12 years). The Pearson's correlation coefficient was used to analyze the relationship between the cephalometric trigeminal and conventional variables. The significance was set at p < 0.05. The Senegalese mesoface appear to be more retrusive and more divergent when compared with European standard. Regarding sexual differences, TRG-ESO-CPA angle shows significant sexual dimorphism, the maxillary mesofacial prognathism is more important for boys (p = 0.04). When compared to the < 12 years subgroup, the > 12 years subgroup shows significant increase in the mesofacial prognathism and a decrease in the mesofacial divergence but the difference was not significant. Maxillary and mandibular mesofacial prognathism were positively correlated respectively with SNA (r = 0.22; p = 0.021) and SNB (r = 0.28; p = 0.004). The latter were in addition negatively correlated with the mandibular angle Ar-Go-Me (r = - 0.20; p = 0.041). Lastly, the mesofacial divergence angle is positively correlated with the mandibular angle (r = 0.20; p = 0.044) and negatively correlated with SNB (r = - 0.22; p = 0.027). The trigeminal analysis based on true anatomical skeletal points provides a good way to assess facial structures and could allow proper forecasting of the dento-alveolar compensation and complement reliably conventional cephalometric analysis.

The Use of Spatial Filtering Techniques: The Spatial and Space-Time Structure of German Unemployment Data

Socio-economic interrelationships among regions can be measured in terms of economic flows, migration, or physical geographically-based measures, such as distance or length of shared areal unit boundaries. In general, proximity and openness tend to favour a similar economic performance among adjacent regions. Therefore, proper forecasting of socio-economic variables, such as employment, requires an understanding of spatial (or spatio-temporal) autocorrelation effects associated with a particular geographic configuration of a system of regions. Several spatial econometric techniques have been developed in recent years to identify spatial interaction effects within a parametric framework. Alternatively, newly devised spatial filtering techniques aim to achieve this end as well through the use of a semi-parametric approach. Experiments presented in this paper deal with the analysis of and accounting for spatial autocorrelation by means of spatial filtering t! echniques for data pertaining to regional unemployment in Germany. The available data set comprises information about the share of unemployed workers in 439 German districts (the NUTS-III regional aggregation level). Results based upon an eigenvector spatial filter model formulation (that is, the use of orthogonal map pattern components), constructed for the 439 German districts, are presented, with an emphasis on their consistency over several years. Insights obtained by applying spatial filtering to the database are also discussed.

Preventive Control of Powdery Mildew Disease of Mango

Oidium mangiferae Berthet was found to be associated With the powdery mildew disease of mango. The air- borne conidia are released from the old tissue harboring the dormant fungal hyphae under favorable weather conditions, which produce the disease. Proper forecasting of release of airborne innoculum significantly reduced the required number of sprays needed for chemical control. Spore traps were used to monitor the concentration of airborne conidia during the months of February, March and April 1996 and l997. Daily temperature and relative humidity were noted and the spore counts from the spore traps were correlated to the meteorological data. There was a positive trend between rising temperature, lowering relative humidity and number of spores in the air alter a low temperature, high humidity and cloudy spell of weather. The maximum spore occurrences were noted around 25°C and relative humidity of 40-60%. It took 5-8 days for the emergence of disease symptoms after the first detection of airborne conidia. Ten fungicides were tested on three mango varieties (Langra, Dashehari, and Anwar Retol). The preventive sprays at the stage of first detection of air born conidia were effective in controlling the disease. Optimal timing of two sprays of fungicide were sufficient to provide preventive control (&gt;90%). The susceptibility of inflorescence varied with its developmental stage. Proper forecasting reduced the number of sprays from 7 to 2 or 3. There was no varietal difference in incidence of the disease or response to fungicide applications. During the course of this study, we identified seedling plants which consistently showed resistance to powdery mildew.

The Forecasting of Demand for New Products

The principal aim of the economic reform that is being implemented in our country — increasing the effectiveness of social production — presupposes a painstaking analysis of demand for new products. When indices of the volume of commodities sold, of profit and the level of profitability are pushed into the forefront, the performance of the manufacturing plant depends, to a large extent, on the volume of sales, which is determined by the demand for the commodities produced. This is why of late more and more importance is attached to the proper forecasting of demand for various items and to planning the sale of commodities on this basis. Accordingly, the development of scientific methods for such forecasting becomes an imperative necessity.