Forecast/forecasting objective

The extent of knowledge of the forecast object and processes in it actually determine the forecasting methods and reliability of their results. A distinction should be observed between the state of knowledge of the forecast area and those processes which affect it. 

Its substance is in setting problem forecast objectives, i.e., questions, which are necessary to answer through modeling. As a rule, they have an ecological or research nature. In the former case the problem to be solved is associated with underground water or geological environment quality protection as a whole. In the latter case, with the study of hydrogeochemical environment, its processes and their role in formation economic mineral deposits. 

For instance, V.N. Ozyabkin (1995) subdivides them depending on the complexity and dimension of the forecast object. J.Rubin (1983), W. Kinzelbach (1992), S.R. Kraynov et al. (2004) base the classification on phase uniformity of the medium and velocity of chemical processes. In this connection they distinguish thermodynamical, transport and kinetic models. In Europe and the USA are broadly used classifications based on typization of local problems (Chen Zhu, Anderson G., 2002, Bethke C. M., 2008, etc.). In connection with this all hydrogeochemical models are subdivided there into three groups speciation-solubility models or batch models, reaction path modelsor mass transfer models reactive transport models or couplet mass transport models. In the second group of this classification is non-uniquely identified the role of mass transfer kinetics. 

Such stability depends to a significant degree on the interrelation of discretization steps for the forecast object in space and time. There are certain restrictions of such interrelations. If this restriction is exceeded, numerical... 

No accuracy measure is generally applicable to all forecasting problems due to variation in forecasting objectives and data scales (De Gooijer and Hyndman, 2006 Hyndman and Koehler, 2006). Let denote the observation at time t and F, denote the forecast of Y. Then define the forecast error e=Y F. In this chapter,... 

Kahn (2006) provides direction on how new product forecasting should be performed. He states that the first step is to establish the forecasting objective, as this will clarify the purpose and intent of the forecast so that a meaningful forecast can be made. Once the forecasting objective is established, consideration is needed regarding the forecasting level, time horizon, interval and form. 

The reservoir model will usually be a computer based simulation model, such as the 3D model described in Section 8. As production continues, the monitoring programme generates a data base containing information on the performance of the field. The reservoir model is used to check whether the initial assumptions and description of the reservoir were correct. Where inconsistencies between the predicted and observed behaviour occur, the model is reviewed and adjusted until a new match (a so-called history match ) is achieved. The updated model is then used to predict future performance of the field, and as such is a very useful tool for generating production forecasts. In addition, the model is used to predict the outcome of alternative future development plans. The criterion used for selection is typically profitability (or any other stated objective of the operating company). 

The way many companies identify resource requirements is to solicit resource budgets from each department covering a 1 to 5 year period. However, before the managers can prepare budgets they need to know what requirements they will have to meet. They will need access to the corporate plans, sales forecasts, new product development plans, marketing plans, production plans, etc. as well as the quality policies, objectives, and procedures. 

Production planning includes considerations on production objectives over a certain time horizon given marketing forecasts for prices and product demands, equipment availability, and inventories. This is a macrolevel problem of the allocation of production capacity, time, product inventories, and labour and energy resources, so as to determine the production goals that maximize the total profit over an extended period of time into the future (e.g. a few months to a few years). 

According to Galilei, the observation of natural phenomena using suitable measuring instruments provides certain numerical values which must be related to one another the solution of the equations derived from the numbers allows us to forecast future developments. This led to the misunderstanding that knowledge could only be obtained in such a manner. The result was deterministic belief, which was disproved for microscopic objects by Heisenberg s uncertainty principle. On the macroscopic scale, however, it appeared that the deterministic approach was still valid. Determinism was only finally buried when deterministic chaos was discovered. 

It is extremely difficult to forecast what the Spanish health system of even the near future will be like, particularly if it continues to be anchored in the dynamics offered today by national health services services as if they were just another administrative service, national implying a strong tendency towards uniformity and health denoting an intention that is not always translated into the best integration (for instance, between ultimate objectives and the provision of services, or between health sector policies and all the other economic and social sector policies). 

As the main theme of this meeting is to assess and consolidate past achievements in various key areas of inorganic/organo-metallic chemistry, with the objective of gazing deep and hard into the futuristic chemical crystal ball of the 21st century, the purpose of my presentation will be to focus attention on pivotal developments in the field of transition metal atom/metal cluster chemistry over the past decade and then to attempt to project and forecast some of the more promising directions that the area is likely to follow in the years ahead. 

MODELKEY (http // www.modelkey.org/) was an EU-funded project (2005-2010) within the sixth framework programme (FP6-2005-global-4, Topic II 3.1) that aimed to deliver models for assessing and forecasting the impact of environmental key pollutants on freshwater, and marine ecosystems and biodiversity. The main objectives of MODELKEY were ... 

One of the central objectives of the study of chemistry is sufficient knowledge to permit the forecast of the chemical and physical properties of a substance directly and reliably from its structure. This objective has been achieved to a remarkable degree for the host of isolable compounds that have been prepared and investigated. These findings have been codified in generalizing... 

This report begins with a brief review of the electronic and structural features that underlie all of carbene chemistry. Next, we introduce the set of related aromatic carbenes that are the basis for our dissection of the effects of structure on carbene properties. The chemical and spectroscopic techniques and procedures used to probe these carbenes are described and explained briefly in the succeeding section. Then, the results of the application of these probes to the chosen carbenes are presented. Finally, the revealed relation of a carbene s structure to its chemical and physical properties is placed within the predictive framework of molecular orbital theory. Our objective in this report is to present sufficient information to permit us to forecast the properties of an aromatic carbene directly and reliably from its structure. 

The stated objective of this report was to present sufficient data about aromatic carbenes to permit the forecast of their properties directly and reliably from their structures. This has been accomplished to a reasonable degree. Coupling of the theoretical framework with the experimental measurements allows confident prediction of the outcome of many chemical reactions. The rates of the important processes controlling aromatic carbene behavior can be estimated, and thus even yields can be forecast in many... 

If the object is a forecast interval the desired balance level is considered by estimating the balance resulting from the actual existing objects (quants, stocks, forecasts) and if necessary generating only the difference to the desired balance level. Quantities can be ... 

Future capital costs considered in the objective function rely on future capital values - in this scope future inventory values. The planning of future inventory values in all future periods and in all network locations is a complex task. As described in the requirements, future inventory value is determined by the future product values of the products on stock. These product values change, if the included material costs of the product change, which is regularly the case due to volatile raw material prices. The task now is to calculate the future inventory value throughout the value chain network and product steps considering the raw material price forecast for the planning horizon. The problem is illustrated in fig. 57. 

In this study, operational risk was accounted for in terms of variance in both projected benefits, represented by first stage variables, and forecasted demand, represented by the recourse variables. The variability in the projected benefit represents the solution robustness where the model solution will remain close to optimal for all scenarios. On the other hand, variability of the recourse term represents the model robustness where the model solution will almost be feasible for all scenarios. This approach gives rise to a multiobjective analysis in which scaling factors are used to evaluate the sensitivity due to variations in each term. The projected benefits variation was scaled by 0i, and deviation from forecasted demand was scaled by 02, where different values of 0i and 02 were used in order to observe the sensitivity of each term on the final petrochemical complex. The objective function with risk consideration can be written as follows ... 

The objective function of a supply network design model can either minimize costs or maximize profits. In practice the production function is often required to assume that all forecasted demands have to be met. In this constellation cost minimization and profit maximization lead to identical results and consequently cost minimization models are used. From an economic perspective this simplification can be justified in cases where a high share of fixed costs allows the assumption that any product sale con-... 

The objective of order and demand management is to forecast future sales as precisely as possible, manage customer orders from entry to delivery, and consolidate forecast and orders with supply chain inventory requirements in order to generate a holistic demand plan for purchasing, production, and distribution planning. 

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