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- 저자 : A.B.M. Salman Rahman (검색결과 6 건)
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A.B.M. Salman Rahman,이명배,신창선,Saravanakumar Venkatesan,임종현 (사)한국스마트미디어학회 2022 스마트미디어저널 Vol.11 No.5
Honey is one of the most significant ingredients in conventional food production in different regions of the world. Honey is commonly used as an ingredient in ethnic food. Beekeeping is performed in various locations as part of the local food culture and an occupation related to pollinator production. It is important to conduct beekeeping so that it generates food culture and helps regulate the regional environment in an integrated manner in preserving and improving local food culture. This study analyzes different types of environmental factors of a smart bee farm. The major goal of this study is to determine the best prediction model between the linear regression model (LM) and the support vector regression model (SVR) based on the environmental factors of a smart bee farm. The performance of prediction models is measured by R2 value, root mean squared error (RMSE), and mean absolute error (MAE). From all analysis reports, the best prediction model is the support vector regression model (SVR) with a low coefficient of variation, and the R2 values for Farm inside temperature, bee box inside temperature, and Farm inside humidity are 0.97, 0.96, and 0.44.
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An Analysis Study Based on Linear Regression Model for Changes of Fruit Size over Plum Diseases
A.B.M. Salman Rahman,Ragu Vasanth,이명배,박장우,조용윤,이명훈,신창선 한국지식정보기술학회 2018 한국지식정보기술학회 논문지 Vol.13 No.5
There are different types of diseases occur in plants and fruits due to the changes of not only the climate, weather, and seasons, but also the environmental factors like temperature, humidity, and rainfall etc. Diseases can change the structure of plants, fruits and also crops. The influence of plants and fruits disease affects our agriculture industry and agriculture sector. Diseases can interrupt our plant’s growth, fruits growth, production growth, and also makes an effect on economic growth all over the world. Farmers have a lot of experience in detecting problems and also they can identify the diseases in various plants. They can easily take care or actions for environmental factorial diseases but sometimes it’s not working. Technologies can support farmers to make their methods more reliable to improve farmer’s crops and fruits quality for a good production. Therefore in this study, we analyse different types of plum plant diseases and then use the linear regression model to know the condition of plum fruit size using plum growth, plum length and plum width. In result and discussion, we identify the environment factorial diseases in plum and also make a decision by verifying the plum fruits size after diseases occurred in Plum Plants.
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A.B.M. Salman Rahman,이명배,Vasanth Ragu,조용윤,박장우,신창선 한국지식정보기술학회 2019 한국지식정보기술학회 논문지 Vol.14 No.3
Strawberry is one of the most well-liked fruits all over the world, and strawberry productions is rapidly rising as one of the most healthy economies all over the world. Due to the high demand for strawberries, greenhouse strawberry cultivation is increasing rapidly and farmers are using different types of methods for greenhouse cultivation to get high productions. The aims of this study are to find out the high production rate of the strawberry based on nutrient solutions with water flow rate. Farmers use a different amount of water nutrient solutions for strawberry production but mostly they don’t know how much nutrient solutions with water flow is good for getting high production because of giving the high amount or less amount of nutrient solutions with water flow are always not good or bad for productions. Farmers have to know about the amount of nutrient solutions with water flow for getting good productions and now this is the high time to support farmers for increasing their strawberry productions by giving technological support. Therefore, in this study, we analyze the production rate of strawberries based on the nutrient solutions with water flow rate of strawberries in every bed. Finally, through the results and discussion by using the support vector regression model we find out that how much nutrient solutions with water flow should be needed to obtain high yielding of strawberries.
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A.B.M. Salman Rahman,이명배,Vasanth Ragu,임종현,조용윤,박장우,신창선 한국지식정보기술학회 2019 한국지식정보기술학회 논문지 Vol.14 No.3
Analysis and modeling of industrial energy are currently a time-insertion process because more and more energy is consumed for economic growth in an industrial factory. Industrial energy consumption analysis and prediction play a very important role in improving the energy utilization rate to make profitable things for industrial companies or factories. Industrial factory owners are also starting to realize the importance of energy analysis and predictions to make a plan for better energy utilization for their factories. So, this is the high time to work as a technological supportive hand with an industrial factory in order to improve their energy utilization for making some profitable things for industrial organizations and also for our society. It is not so easy process to analyses energy and realizes accurate predictions of industrial energy consumption. Therefore, this study deals with analysing total usages of 24-hours energy consumption for every month and also total usages of energy for the year 2017. We find out the difference between total usages of energy and demands of energy for the year 2017. We make relation curve between per-day usages of energy and different types of materials weight for different types of manufacturing product, and also make a relation curve between per-day usages of energy, demands of energy and total materials weight for manufacturing products for the year 2017. We use the correlation method to find out the relationship of usages of energy with different types of materials weight for manufacturing products. Finally, we find out the total usages of energy for manufacturing every product and make a decision about the energy utilization.
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Identification of Environmental Factors in Fruit Disease by Logistic Regression
Vasanth Ragu,이명배,이명훈,A.B.M. Salman Rahman,박장우,조용윤,신창선 한국지식정보기술학회 2018 한국지식정보기술학회 논문지 Vol.13 No.5
Plant diseases are one of the most significance issues in agriculture fields. The diseases destroy fruits and are decreased the production rate. They also decrease the economic growth in worldwide and increase the demand about preventing plant diseases. The major cause of plant diseases is climate changes, weather conditions and environmental factors. To prevent the diseases, we need to identify the plant diseases about corresponding environmental factors. In this study, we analysis the plum data and identify the plant diseases with corresponding environmental factors by using Logistic Regression model. The first process is to identify the number of diseases and its type, and then implement Logistic Regression to predict the diseases by using environmental factors as inputs. Finally, we compare the actual value of diseases with predicted value of diseases, and need to check the accuracy of diseases by using correlation method. We also find the environmental factors for the reasons to forms more diseases. In result and discussion, it would be clearly explained about the plum diseases and their environmental factors.
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