• Title/Summary/Keyword: Agricultural machines

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Design of Management System for Registering Agricultural Machine Using Blockchain (블록체인을 활용한 농업기계 등록 관리 시스템의 설계)

  • Son, Yong-Bum;Kim, Young-Hak
    • The Journal of the Korea Contents Association
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    • v.19 no.12
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    • pp.18-27
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    • 2019
  • Through the technology of the 4th industrial revolution, agricultural machinery is becoming increasingly intelligent, and the machine is replacing the role of farmer manpower as a whole. However, safety accidents caused by careless use of agricultural machines and theft accidents due to the difficulty of keeping them are increasing every year. Because agricultural machines do not manage the history of events and accidents unlike automobiles, they are often used for crime. There is also no way to cope with the issues if there happens issues on agricultural machines. In this paper, we propose the system based on block chain which can manage the history of the agricultural machinery by registering the chassis number at the same time when purchasing the agricultural machinery. Since this system contains the history of accident and repair information about the owner's agricultural machinery, it is possible to trace back even if a theft occurs. The proposed system also allows buyers to secure transactions by providing reliable data through inquiry of this system when trading in the secondary market in the future.

NIR DIODE ARRAY SPECTROMETERS ON AGRICULTURAL HARVEST MACHINES OVERVIEW AND OUTLOOK

  • Rode, Michael
    • Proceedings of the Korean Society of Near Infrared Spectroscopy Conference
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    • 2001.06a
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    • pp.1172-1172
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    • 2001
  • Compact Near Infrared Diode Array Spectrometers offer new possibilities for on line quality assurance in the agricultural sector. Due to their speed and complete robustness towards temperature fluctuations and mechanical shock Diode Array Spectrometers are suitable for the use on Agricultural Harvest Machines. The growing consumer consciousness of food quality in combination with falling manufacturing prices demands procedures for an effective quality control system. The various conventional types of NIR instruments which have so far been used in laboratories are unsuitable for mobile applications under the rough conditions of field cropping not only because of their slow speed of measurement but also because of their shock sensitive filter wheels and monochromators necessary for fractionating polychromatic light. Another advantage of the on line use is the reduction of the sampling error because of the continuously measurement of the whole product. Considering the large economic importance of the dry matter content on agricultural products it is of particular advantage that water belongs to those constituents which are most easily assessed in the near infrared. While other constituents of economic importance such as starch, oil and protein in grains and seeds have a much lesser effect on NIR signals, their contents can nonetheless be assessed with high analytical precision on freshly harvested grains and seeds. In the last years several applications for on line quality assessment on harvesting machines were developed and tested. The talk will give an overview and outlook on existing and future possibilities of this new field of NIR applications.

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Prediction of Soil Moisture with Open Source Weather Data and Machine Learning Algorithms (공공 기상데이터와 기계학습 모델을 이용한 토양수분 예측)

  • Jang, Young-bin;Jang, Ik-hoon;Choe, Young-chan
    • Korean Journal of Agricultural and Forest Meteorology
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    • v.22 no.1
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    • pp.1-12
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    • 2020
  • As one of the essential resources in the agricultural process, soil moisture has been carefully managed by predicting future changes and deficits. In recent years, statistics and machine learning based approach to predict soil moisture has been preferred in academia for its generalizability and ease of use in the field. However, little is known that machine learning based soil moisture prediction is applicable in the situation of South Korea. In this sense, this paper aims to examine 1) whether publicly available weather data generated in South Korea has sufficient quality to predict soil moisture, 2) which machine learning algorithm would perform best in the situation of South Korea, and 3) whether a single machine learning model could be generally applicable in various regions. We used various machine learning methods such as Support Vector Machines (SVM), Random Forest (RF), Extremely Randomized Trees (ET), Gradient Boosting Machines (GBM), and Deep Feedforward Network (DFN) to predict future soil moisture in Andong, Boseong, Cheolwon, Suncheon region with open source weather data. As a result, GBM model showed the lowest prediction error in every data set we used (R squared: 0.96, RMSE: 1.8). Furthermore, GBM showed the lowest variance of prediction error between regions which indicates it has the highest generalizability.

Design of Agricultural Machine Sharing System Based on Blockchain (블록체인 기반 농업기계 공유 시스템 설계)

  • Son, Yong-Bum;Kim, Young-Hak
    • The Journal of the Korea Contents Association
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    • v.18 no.11
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    • pp.55-62
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    • 2018
  • Many domestic and international countries recently apply the blockchain technology to its related application fields. Not the enterprise-centered economy, the concept of the sharing economy which is controlled by individuals has been expanded. However, the development of the necessary system to realize the sharing economy in the agricultural sector has still been insufficient. Because the agricultural machinery rental business in the recent agricultural policies is managed by the government and the local government keeps and provides limited quantities and resources, its operation system has several problems. In case of high-priced agricultural machines, the machines can not be supplied adequately at the right time due to the limited quantities during the busy farming season. This paper proposes the sharing system that individual owners rent their agricultural machinery to growers using the blockchain technology. Thus, the proposed system provides the distributed method to solve agricultural machines of a lack of resources and also gives the secure service to all the growers.

APPROXIMATE SOLUTIONS TO ONE-DIMENSIONAL BACKWARD HEAT CONDUCTION PROBLEM USING LEAST SQUARES SUPPORT VECTOR MACHINES

  • Wu, Ziku;Li, Fule;Kwak, Do Young
    • Journal of the Chungcheong Mathematical Society
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    • v.29 no.4
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    • pp.631-642
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    • 2016
  • This article deals with one-dimension backward heat conduction problem (BHCP). A new approach based on least squares support vector machines (LS-SVM) is proposed for obtaining their approximate solutions. The approximate solution is presented in closed form by means of LS-SVM, whose parameters are adjusted to minimize an appropriate error function. The approximate solution consists of two parts. The first part is a known function that satisfies initial and boundary conditions. The other is a product of two terms. One term is known function which has zero boundary and initial conditions, another term is unknown which is related to kernel functions. This method has been successfully tested on practical examples and has yielded higher accuracy and stable solutions.

Developed and implementation of a knowledge acquisition methodology for seed material processing expert systems

  • Arkhipova, Paper I.
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 1996.06c
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    • pp.679-684
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    • 1996
  • The work was aimed at realize the problem of seed processing . Solving this problem it was ascertained that the existing mathematical methods are reliable enough, but they are used practically very seldom. The work offers to use the expert system technology which allows to solve problems connected with practical knowledge of experts in the region of investigation effectively. The method of knowledge structuring and analizing as well as technique of knowledge acquisition which is necessary for realization of this technology are worked-out in the work. As the result applying the worked-out method the prototypes of the expert system (ES) are created : -ES " Sieves " ; research prototype for the sieve choice for the seed sorting machines -ES " Diagnostics " ; displaying prototype for the technological determination of action disrepair of seed sorting machines.

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Current Trends in the Development of Fruit Sorters in Japan

  • Maeda, Hironu;Mizuno, Toshihiro;Kouno, Yoshihide
    • Proceedings of the Korean Society for Agricultural Machinery Conference
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    • 1993.10a
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    • pp.1302-1311
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    • 1993
  • In the 90 years or so since the beginning of the 20 th century , orchard growing and agricultural fields in Japan have undergone considerable change in terms of production volume, a seen in Fig. 1. as this change in volume progressed, sorting and packing machines have also grown from the first wooden tools, almost too simple to be called " machines" into sophisticated devices that bring together diverse technologies such as machinery , electronics, and optics. Nowadays, Japan/s agricultural industry is facing unprecedentedly serious labor shortage and the rapid aging of its experienced growers and producers, In additions, Japan has changed from a society oriented towards high-volume production and consumption to a more selective society which prefers smaller volume with the tastes of naturally ripended produce. With consumer trends changing there is a new demand on the part of growers for equipment that can not only measure the external quality of produce , but can measure inte nal quality as well.

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Estimating Demand Functions of Tractor, Combine and Rice Transplanter (트랙터, 콤바인, 이앙기의 수요 함수 추정)

  • Kim K.;Park C.K.;Kim K.U.;Kim B.G.
    • Journal of Biosystems Engineering
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    • v.31 no.3 s.116
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    • pp.194-202
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    • 2006
  • Using a multi-variable linear regression technique and SUR(seemingly unrelated regression) model, the demand functions of tractor, combine and rice transplanter were estimated. The demand was regarded as an annual supply of each machine and modeled as a function of 11 independent variables which reflect the actual farmer's income, actual prices of farm machines, previous supply, previous stock, actual amount of available subsidy, actual amount of available loan, arable land, import of farm machines and rice price. The actual amount of available loan affects most significantly the demand functions. The actual farmer's income, actual farmer's asset, loan coverage, and rice price affect the demand positively while prices of farm machines and import negatively. The annual demands of tractor, combine and rice transplanter estimated using the demand functions were also presented over the next 4 years.