Assessing forecasting performance

This section presents an in-depth discussion on the forecasting performance of the proposed HI model. The forecasting performance of the proposed HI model is first analyzed based on the experimental results presented in Section 9.4. Further analysis is then conducted to validate the superiority of the proposed model over other models based on public benchmark data sets. The effectiveness of the model s components, including the heuristic fine-tuning process, data preprocessing component and HI forecaster, is also analyzed in this section. 

2 Further analysis on forecasting performance of proposed model 

According to the forecasting results based on real fashion retail data and benchmark data from M3 competition, it can be concluded that the proposed model is widely applicable, since it is capable of generating accurate forecasts for a variety of time series with irregular patterns as well as strong seasonal patterns. 

Exterrsive experiments were condircted to validate the proposed HI model in terms of real fashion retail data The experimental resirlts have shown that the HI model can tackle the medium-term sales forecasting problem effectively, which also demorrstrates that the proposed model can provide much superior performance over traditional ARIM A models and two recently developed sales forecasting NN models. A further experiment was presented based on seven irregular annual data sets from M3 competitiort, which further validates the effectiveness of the proposed HI model and shows that the HI model is more powerful to tackle the time series with sufficient sample data. Firrthermore, since the time series tackled in this chapter involve various patterns such as irregirlarity and seasonality, the proposed model is widely applicable and can be easily extended to solve other forecasting problems with similar time-series patterns. 

The proposed model provides forecasts based only on historical sales data, which cannot reflect the effects of exogenoits factors, such as weather and economic indexes, on fashion sales. Futirre research will focus on investigating mirltivariate HI forecasting models cortsidering the effects of various exogenous changes on fashion sales. Moreover, it is also a worthwhile research direction to 

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Dressman JB. Dissolution testing of immediate-release products and its application to forecasting in vivo performance. In Dressman JB, Lennemas H, eds. Oral Drug Absorption Prediction and Assessment. New York Marcel Dekker, 2000 155-181. 

Standards and method statements envisage geotechnical survey performance only in the pre-construction period that leads to insufficient forecasting of the geotechnical conditions for the main pipeline construction in mountainous areas. Therefore accurate quality assessment of the survey is excluded which is crucial for the mitigation of adequate environmental risks in the design and development phase. 

Sargent and Lundy LLC (2003). Assessment of Parabolic Trough and Power Tower Solar Technology Cost and Performance Forecasts. National Renewable Energy Laboratory (NREL). 

ABSTRACT At present, researches on the relationship between coal mine safety input and safety performance focus on the static description. Results of the assessment on these studies lack in follow-up and dynamic management. In this paper, based on the analysis of factors that have impacts on coal mine safety performance in the process of coal production, one model about the relationship between coal mine safety input and safety performance is established using a system dynamics approach. In the process of computer simulation, coal mine safety performance is dynamically forecast by changing the initial safety level value and safety input increase rate of factors which affect system safety performance. The results show that the safety level of coal mine enterprises in the early period influences the coal mine expectant safety performance. The safety level of human factors and management factors in the coal mine enterprises is a positive correlation of coal mine safety performance. These provide a theoretical basis for management decision-making. 

The PIVIT applies virtual instrument technology to assess, analyze, and forecast clinical, operational, and financial performance indicators. Some examples include applications which profile institutional indicators (i.e., patient days, discharges, percent occupancy, ALOS, revenues, expenses, etc.), and departmental indicators (i.e., salary, nonsalary, total expenses, expense per equivalent discharge, DRGs, etc.). Other applications of PI VIT include 360° Peer Review, Customer Satisfaction Profihng, and Medical Equipment Risk Assessment. 

While there are several possible measures of performance of a humanitarian relief supply chain, one approach, suggested by Fearon [37], is to compare an actual outcome with the counterfactual outcome. In such an approach, the question is whether the humanitarian intervention did in fact improve the system in terms of lives saved, diseases avoided, crop failure averted, market functionality maintained, and so on. But other suggestions focus on the success of the appeal coverage, lead time between donation and delivery of aid, financial efficiency and assessment accuracy. Each of these metrics focuses on the process of forecasting the aid required and garnering the resources and then efficiently dehvering the aid while respecting the planned humanitarian space. 

In this section, it will be performed a literature review for each one of the six categories of Product Lifecycle management - New Product Forecast, Supply chain Approach for New Product, Risk Assessment and Management, Product Tracking Visibility, Portfolio Optimization, Senior Management Support. This review allowed identify the DDSC characteristics for each category which was used to develop the five level maturity model. 

Thus far, we provided a characterization of the forecast evolution and the forecasting errors associated with the estimates of the lead-time demands. As we shall see in the next section, this lays the foundation for devising an inventory policy for the channel, and for assessing the overall supply chain s cost performance. Using this tool, one can easily compare between the three settings -LMI, SMI, and CFAR (see 6.4 below). 

ANN has the ability to handle imprecise and fuzzy data they can work with continuous, categorical and binary data without violating any assumptions. As assessment of probability for landslide occurrence is performed through the forecast of... 

Sargent Lundy LLC Consulting Group. Assessment of parabolic trough and power solar technology cost and performance forecasts, October 2003, National Renewable Energy Laboratory, US. 

Condition assessment of civil structures is a task dedicated to forecasting future structural performances based on current states and past performances and events. The concept of condition assessment is often integrated within a closed-loop decision, where structural conditions can be adapted based on system prognosis. Figure 1 illustrates a particular way to conduct condition assessment. In the process, various structural states are measured, which may include excitations (e.g., wind, vehicles) and responses (e.g., strain, acceleration). These measurements are processed to extract indicators (e.g., maximum strain, fundamental frequencies) of current structural performance. These indicators are stored in a database, and also used within a forecast model (e.g., time-dependent reliability, Markov decision process) that will lead to a prognosis on the structural system, enabling optimization of... 

Reliability predictions are commonly used in the development of products and systems to compare alternative design approaches and to assess progress toward achieving reliability design goals. They are often criticised as not being accurate forecasts of field reliability performance because they do not usually account for all the factors that cause field failures. 

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