Summary
Author presents necessary conditions to create decisional- operational model of food economy system. The main condition is that economy is one sum of functionality which is directly related to rest of elements of economy. The purpose of model is to help to undertake both operational and strategic decisions. It takes under considera-tion changes which are in economy and its environment and updates info continu-ously. Tasks set to this model will have to use knowledge from different scopes of science like: mathematics, economy or computer sciences.
Keywords: model, data bases, food economy 1. Introduction
Changes in economical reality in XXI century are made so quick and dynamic that it is hard to catch the right moment, on which we can base as on something stable especially when we made strategic or operational decisions. Due to this fact there comes necessity to create stable and intel-ligent model of reality, which will be up-to-date with its knowledge, which will analyze and de-crease the risk of insure and which will allow preparing conditions accurate to undertake decision. New economy model can be described not only by the most important issues but also by mak-ing the characteristic of its participants. Its characteristics were not well known in economy and are as follows: price of its assets is not as big as its general capital. Knowledge of employees, knowledge of teams, knowledge of organization is strategic point to win the market competition. [Borkowski B., WoĨniakowski M. 2006].
It is new challenge to connect traditional management and data mining for getting the detailed solutions of given problem. Creation of that kind of model for whole economy of course is possi-ble but it takes time and money, it needs to solve propossi-blem with getting data from different sources so in this paper it was limited to modeling the food economy. In years 1989-1992 this sector of economy was reformed in very strict way. Many state farms were closed without checking its condition, many people who lived in villages lost work. Social and economical problems of polish village are until today one of the hardest to solve. Proposed system should provide possible solu-tion in as much as possible cautious way with respecting as less as possible risk of decision.
After deep analysis of accessible on market methods for analyzes it is sure that for purpose of creation decisional- operational system the best choice will be the one which will base on neuron networks. Multi-functionality of neural networks are used with success in stock exchange progno-sis or sell prognoprogno-sis is giving good base for theprogno-sis that neural networks in our model will be the most optional choice and it will work correct. In author opinion the NN would be the most effi-cient for operating the system.
2. Draft of model of decisional-operational system
Model is a tool which needs to have implemented specified standards. These standards are also technical one. For our model we need:
a) two databases
b) user interface connected to request analysis system
c) system based on neural network, which analyze data from request and database d) system of initial statistic analysis
Img. 1 Model of operational-decisional system Source: Own project
Initial statistic analysis processed data database no. 2 R eq u es te r
request about American bilberry
not processed data
database no.1
Data process-ing and analy-sis based on
neuron net-work user interface
answer provided by sys-tem
When we take food economy as one system, one functional sum, we can think about it as on whole system on which entrance data have influence and system has influence on environment by exit data.
Precisely chosen entrance data creates basics to define condition of proper functionality of food economy. It also shows its connections with other elements of economy. Database would be up-dated continuously also by providing there results of chosen decisions.
Img. 1 Connections between food economy and environment Source: Own project
2.1. Database no. 1
collected data in database should be related to all elements which have influence on food economy both in direct and indirect way. Example kinds of data are as follows:
amount of population uses of food products national economy politics
uses of productive limits (got by international commitments) prices of petroleum
average salary
amount and kinds of exported and imported products prices of sell and buy of products in other countries national Financial politics with focus on village current technical and informational structure
Data which are direct related to agriculture and farming are information containing: land acreage, its quality, current and previous farmed plants, atmospheric conditions, amount and structure of possessed animals, amount of people which work directly in farming divided into age, sex groups, etc. Level of information details should be chosen carefully during planning process.
That kind of data will be put into general database marked on our model (img 1) as “database no. 1”. This database is first database which collects all data from different sources with different level of its importance. It should be sorted by some defined conditions and should be updated continu-ously. Only this will guarantee the highest level of system efficiency.
food econonomy
exit data
entrance
data
environment
Creation of that kind of wide database is possible by using currently existing databases like from statistical departments, year-books, ministry of agriculture, ARR, ARiMR, IRWiR, IGiR, minis-try of economy and many others administrative departments.
2.2. Initial analysis and database no. 2
New and still growing part of computer sciences is section related to systems which are look-ing for knowledge by uslook-ing big amount of data. This branch of IT is known as “Knowledge Dis-covery in Databases - KDD”. It is strictly related to Data Mining. Knowledge is provided auto-matically and verified by computer system. The role of expert is review and mark given knowl-edge by using rules. Expert checks if result is acceptable using special statistical indicators. [Budz-iĔski R., Szaranek A. 2006].
Data in “database no.1” are in not equalized. They differ because of not one common source. Using different statistical methods system will analyze data and choose the one which are neces-sary critical to undertake any decision. Result of this analysis will be put into second database (“database no. 2”), which should be the base for entrance data for neuron network.
3. User interface and neural network system
On collected material there will be performed preliminary processing under specific problem e.g. is it profitable to take economic activity in subject of farming American’s bilberry in city X, with known economic conditions in country and abroad, and also other competitors in closest and far region. The request will be sent by user interface. System will request the critical for decision information. This information’s are result of analysis method and collected in “database no.2”. System depending on assigned request will take required data from “database no.2”. It will be-come entrance data for system of neural network.
In our question about American’s bilberry this information’s can be for example quality and amount of ground, size of possible production, climate in context of product requirements. Extra data like analysis the amount of workers, financial conditions or similar farming in region (com-petitors) would be helpful in providing the right answer. Also we provide to the model data about possible costs and profits with that kind of farming. Model should also provide the information with different variants for example how it would look like with bank credit or without, with taking EU founds or not. Every farm has its own specification. Sometimes extra workers are hired and sometimes they can use to work members of own family. Model should mix all data maximal way and provide few answers (few ways) with possible risk.
There is no doubt, that with so many given data, the neuron network will be the one (meaning the most efficient for this project), right solution to perform deep and correct analysis.
Presented dependences will be presented as mathematic functions with taking into considera-tion economical weight of particular variables. These weights will be used in neuron networks. System based on neuron network, after analysis of entrance data will provide as a result exit data which will be provided as an answer to user interface (or will be send by email- depend of set conditions)
Because of complexity system has few critical points, of which its credibility will depend.
1. determine the essential data for making the decision. From the point of view of making decision, some information is not important. During system preparation process it is necessary to determine which information are critical, which are optimal, etc. Providing weight of problems allow for better planning the neural network education.
2. correct recognize and use of statistical methods. Wrong sorted data or wrong counted weights of particular variables will make system work wrong from the beginning
3. correct project of databases. First database is not critical for system. Wrong prepared project of second database may be the cause of problems with retrieving correct entrance data for neuron network.
4. project of the neuron network. Correct analysis of defined problem is necessary. System needs to know how and what kind of data will be provide on entrance and what kind of answer we would like to get what is strictly related to amount of exit data of neuron network. It is necessary to set if in network will be hidden layers (if yes, then how many), how many neurons will be in particular layer. It is also necessary to define how network should learn. Should it be supervised, unsupervised or reinforcement learning.
Proper inclusion for project, the model of management as well as management of knowledge should provide measurable economic effects and also give competitive superiority of polish firms in these sectors.
In early stage of project, researcher search for results of analyses, structures of market occur-rences, dynamics, relations between cause and result, market analyses in area. For this purpose there will be used statistic and taxonomic programs. Its purpose is to be a tool which helps to limit area of search solution on strictly defined area of limiting conditions.
4. Conclusion
There are under consideration two ways of processing the creation of operational-decisional models (which uses databases). First one: group of people who prepare that kind of systems be-lieve, that it must be done on small own databases. Second one: creators perform steps which pro-vide to creation of one system which co-operates with smaller databases. Second choice seems to be more interesting because it takes all possible data from different sources and allows for wide look at problem.
The object of consideration should lead author towards second way of procedure. Author thinks that this way is better, especially that creation of the system for the entire food economy expects from creators big knowledge and skill of knowledge management and construction of conclusions
Bibliography
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