Data Mining Practical Machine Learning Tools and Techniques

In recent years, huge efforts have been made to implement ICT innovations in the agricultural sector in order to increase its competitiveness. The question that can be posed is what depends on the successful implementation of ICT innovations among farmers. Numerous scientific papers were published with the purpose of identifying factors that affect acceptance of particular innovation by users. The aim of this paper was to determine whether the farmer innovativeness inﬂuences the acceptance and the degree of using the Internet and social media by farmer. Additionally, statistically significant correlation between the demographic factors of the farmers and their innovativeness was investigated. The research was conducted using survey method. Descriptive statistics, Correlation analysis using Pearson’s correlation coefficients and Chi-square test were used as statistical methods. Obtained results confirmed the initial hypotheses and based on that recommendations for the creation of a marketing strategy for introducing new ICT solutions in the fled of agriculture are made.

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Farmer innovativeness and its impact on internet and social media adoption

The subject of paper is export competitiveness of food manufacturing of Republic of Serbia during the period 1996-2016. The analysis of export competitiveness was realised by using the following indicators: Revealed comparative advantage (RCA), Competitiveness growth index (RCA1), Index of net business performance (RCA2), Index of contribution to the trade balance (CTB), Grubel-Lloyd index (GLI) and Michaely index (MI). The results show that RCA values were positive in all years, which speaks of comparative advantage of this industry on the domestic market. Since the RCA1 values were higher than one, they revealed export competitiveness. The positive values of RCA2 during the period 2005-2016 bear witness of contribution of food manufacturing in foreign trade balance of Serbian economy. The average value of CTB index was 3.998 and its positive annual values showed that the contribution of food manufacturing in the total trade balance was positive. The change of GLI values pointed to the loss of ability of the sector to create surplus of national trade balance. Positive annual values of MI confirmed the competitiveness of food manufacturing, but also its insufficient specialization.

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Competitiveness of food manufacturing of republic of serbia

Agricultural loans present unutilized bank credit market segment in Serbia. This is not only missed profit opportunity for banks, but also serious deficiency that slows down the development of agriculture and rural areas. Paper uses FADN, NBS and bank balance sheet data in order to analyse supply and demand side of this credit market segment, with the aim to better understand the conditions for its development. Paper recommends better education of producers and lenders. Banks should better understand the requirements of agricultural producers and risks of the production to be able to create tailored credits. Insurance has very important role in specific risk hedging and can facilitate agricultural loans. There is also a need to adjust the conditions for obtaining subsidized loans, while the land size is considered as a key prerequisite for obtaining loans in the situation of large fragmentation of properties.

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The importance of bank credits for agricultural financing in serbia

A mathematical model of a doubly-fed asynchronous generator is defend in the paper, using spatial vector theory, in relation to the reference axis associated with the stator. Expressions for characteristic quantities are derived, and operational characteristics for the torque, active and reactive power, power factor, and efficiency are plotted, from which generator operation is analysed at different rotational speeds. Based on this, possibilities and advantages of using doubly-fed asynchronous generators in wind turbines, for obtaining electrical energy from wind energy, are deduced.

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Characteristics of a doubly-fed asynchronous generator applied in wind turbines

Managing reserves of spare parts for agricultural machinery in agricultural farms represents one of the most important activities in securing smooth functioning, especially having in mind the imperative of continuous agricultural production. Aims of this study were to show how efficiency of the agricultural farms as a business subject can be secured by determining timely purchase of spare parts by using a stochastic model of supplies on one side and reduce the time of malfunction of agricultural machinery on the other. Study of optimal inventory level was conducted in agricultural holdings on the territory Banat in 2015 based on data on spare parts purchase and malfunction of agricultural machinery. Acquired data was related to frequency of defects and the need for spare parts, as well as the price of spare parts, where the data was processed with the use of stochastic model of supplies. The optimal number of spare parts for the observed equipment in the observed period was y*=4 with the probability of 85% that this amount of spare parts will be sufficient for all malfunctions on the equipment to be eliminated, while taking a 15% risk that one or two spare parts will be acquired with emergency procurements in case of extraordinary circumstances. The model of managing supplies represented in such a way provides an opportunity to be easily applied in agricultural farms, where the values of an optimal solution would be effectively got with previously chosen values of suitable parameters, thus minimizing total expected costs, which would include fxed costs, expenses caused by unsatisfied requests, where the time of waiting for the observed equipment to be fxed would be taken into account.

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Analysis of optimal costs for reserves of spare parts for agricultural machines

Data Mining (DM) through data in agroeconomy is a scientifc method that enables researchers not to go through set research scenarioes that are predetermined assumptions and hypotheses on the basis of insignifcant atributes. On the contrary, by data mining detection of these atributes is made possible, in general, those hiden facts that enable setting a hypothesis. The DM method does this by an iterative way, including key atributes and factors and their inﬂuence on the quality of agro-resources. The research was conducted on a random sample, by analyzing the quality of eggs. The research subject is the posibility of classifying and predicting signifcant variablesatributes that determine the level of egg quality. The research starts from the use of Data Mining, as an area of machine studies, which signifcantly helps researchers in optimizing research. The applied methodology during research includes analyticalsintetic procedures and methods of Data Mining, with a special focus on using Supervised linear discrimination analysis and the Decision Tree. The results indicate significant posibilities of using DM as an additional analytical procedure in performing agroresearch and it can be concluded that it contributes to an improvement in effectiveness and validity of process in performing these researches.

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Slobodan Stanojević

Papers

Analysis of optimal costs for reserves of spare parts for agricultural machines

Quality of research results in agro-economy by data mining