• Journal of Power Electronics
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• 제11권4호
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• pp.393-400
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• 2011

The main objective of this paper is to control the speed of Nonlinear Hybrid Electric Vehicle (HEV) by controlling the throttle position. Various control techniques such as well known Proportional-Integral-Derivative (PID) controller in conjunction with state feedback controller (SFC) such as Pole Placement Technique (PPT), Observer Based Controller (OBC) and Linear Quadratic Regulator (LQR) Controller are designed. Some Intelligent control techniques e.g. fuzzy logic PD, Fuzzy logic PI along with Adaptive Controller such as Self Organizing Controller (SOC) is also designed. The design objective in this research paper is to provide smooth throttle movement, zero steady-state speed error, and to maintain a Selected Vehicle (SV) speed. A comparative study is carried out in order to identify the superiority of optimal control technique so as to get improved fuel economy, reduced pollution, improved driving safety and reduced manufacturing costs.

• International Journal of Advanced Culture Technology
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• 제9권2호
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• pp.91-99
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• 2021

In Korea, some pharmaceutical companies and agricultural machine manufacturers associate the length of the credit period with the retailer's order size. This kind of commercial practice is based on the principle of economy of scale from the supplier's point of view and tends to make retailer's order size large enough to qualify a certain credit period break. Also, the credit period allowed by the supplier makes it possible to reduce the retail price expecting that the retailer can earn more profits by the stimulating the customer's demand. Since the retailer's order size is affected by the end customer's demand, it is reasonable to determine the retail price and the order size simultaneously. In this regard, this paper analyzes the retailer's problem who has to decide his sales price and order quantity from a supplier who offers different credit periods depending on his order size. And we show that the retailer's order size large enough to qualify a certain credit period break. Also, it is assumed that the end customer's demand rate is represented by a linear decreasing function of the retail price.

• 아태비즈니스연구
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• 제11권2호
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• pp.207-233
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• 2020

Purpose - The purpose of this paper analyzes the relationship between the Corporate Social Responsibility(CSR) and Corporate Value to estimate whether the characteristics of Firm can change this relationship. Design/methodology/approach - This paper utilizes the total 776 firms' data over the period 2014-2018, and develops a new ESG index which was estimated by PCA. Findings - First, the estimated ESG index implies that Large company has the highest value of CSR, while Medium sized and Small company have the relatively low one. And comparing to the case of 2014, the trend of ESG index in Large company does not decrease in 2018. Second, there is a clear and significant non linear relationship between CSR and corporate value, it implies that the U-shaped exists in the Korean Firms. Such a tendency is mush stronger in the Large company. Third, the new ESG index indicates that it takes more time to increase Firm value in the Medium sized and Small company while there is a high possibility of increasing value in Large company from the little gab between the threshold points and mean value of ESG. Research implications or Originality - The non linear tendency between the Corporate Social Responsibility and Corporate Value is strongly affected by Firm size and the relative high quintile of ESG, but it is less affected by Firm history.

• 한국인공지능학회지
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• 제9권1호
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• pp.21-27
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• 2021

In this Paper, Since the 1990s, Korea's credit card industry has steadily developed. As a result, various problems have arisen, such as careless customer information management and loans to low-credit customers. This, in turn, had a high delinquency rate across the card industry and a negative impact on the economy. Therefore, in this paper, based on Azure, we analyze and predict the delinquency and delinquency periods of credit loans according to gender, own car, property, number of children, education level, marital status, and employment status through linear regression analysis and enhanced decision tree algorithm. These predictions can consequently reduce the likelihood of reckless credit lending and issuance of credit cards, reducing the number of bad creditors and reducing the risk of banks. In addition, after classifying and dividing the customer base based on the predicted result, it can be used as a basis for reducing the risk of credit loans by developing a credit product suitable for each customer. The predicted result through Azure showed that when predicting with Linear Regression and Boosted Decision Tree algorithm, the Boosted Decision Tree algorithm made more accurate prediction. In addition, we intend to increase the accuracy of the analysis by assigning a number to each data in the future and predicting again.

• International Journal of Computer Science & Network Security
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• 제23권9호
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• pp.17-28
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• 2023

Today Agriculture segment is a significant supporter of Indian economy as it represents 18% of India's Gross Domestic Product (GDP) and it gives work to half of the nation's work power. Farming segment are required to satisfy the expanding need of food because of increasing populace. Therefore, to cater the ever-increasing needs of people of nation yield prediction is done at prior. The farmers are also benefited from yield prediction as it will assist the farmers to predict the yield of crop prior to cultivating. There are various parameters that affect the yield of crop like rainfall, temperature, fertilizers, ph level and other atmospheric conditions. Thus, considering these factors the yield of crop is thus hard to predict and becomes a challenging task. Thus, motivated this work as in this work dataset of different states producing different crops in different seasons is prepared; which was further pre-processed and there after machine learning techniques Gradient Boosting Regressor, Random Forest Regressor, Decision Tree Regressor, Ridge Regression, Polynomial Regression, Linear Regression are applied and their results are compared using python programming.

• 문화기술의 융합
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• 제9권6호
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• pp.251-256
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• 2023

국제 경유 가격은 산업, 교통 및 에너지 생산과 같은 여러 분야에서 중요한 역할을 수행하며, 세계 경제와 국제 무역에도 큰 영향을 미친다. 특히, 국제 경유 가격의 상승은 소비자에게 부담을 주고 인플레이션의 원인이 될 수있다. 그러나 기존 연구들은 주로 휘발유에 초점을 맞추어 진행되었다. 따라서 본 연구는 국제 경유 가격 예측 모델을 제안하고자 한다. 이를 위해 다양한 세계 경제 지표들을 활용하여 머신러닝 방법론 중 하나인 선형 회귀 모델로 학습한다. 해당 모델은 세계 경제 지표들과 국제 경유 가격 간의 관계를 명확하게 파악함과 동시에 높은 정확도로 예측한다. 이는 시장 변화를 비롯한 전반적인 경제 흐름 파악에 도움이 될 것으로 기대된다.

• 한국지역지리학회지
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• 제9권4호
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• pp.461-480
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• 2003

본 논문은 대구를 사례로 신도시화 과정을 경제, 정치, 사회문화, 환경 그리고 공간적 측면으로 나누어 고찰하였다. 경제적으로 대구의 산업구조는 제조업 중심에서 서비스산업으로 바뀌었으며, 산업의 특화정도는 조립금속과 정밀 광학분야의 비중이 높아지고 있으나 여전히 섬유산업위주의 단선적 산업구조의 틀을 벗어나지 못하고 있다. 정치적으로 지방자치제의 실시로 지역 간의 경쟁이 첨예해지는 상황에서, 대구 지방정부는 전반적으로 지역여건을 성장주의적 분위기로 이끌어가면서, 약화되는 지역 투자나 생산기능을 확충하기 위해 민 관 학의 연계체계를 구성하여 지역의 현안 문제를 해결하는 경향을 보이고 있다. 사회적으로 구도시 체제에서는 대규모 하드웨어 시설에 많은 투자를 하였으나 신도시 체제에서는 사회문화적 소프트웨어시설에 많은 투자를 하게 되었다. 문화적으로는 기존의 축제가 행정 편의적이고 가시적 축제였다면, 현재의 축제는 시민들과 함께 할 뿐만 아니라 지역경제 활성화에 도움을 주는 축제로 변하고 있다. 환경적으로 지방자치제가 본격적으로 시작되면서 산업기반시설과 혐오시설의 입지로 인해 지방자치단체간의 가치 및 이해관계를 둘러싼 갈등문제가 심각하게 표출하고 있다. 마지막으로 신도시화 과정에서 주거팽창과 공간구조의 불균형적 이용은 토지이용의 비효율성을 야기하고 있다. 이런 무계획적인 도시의 외연적 확산은 직주분리와 사람들의 이동의 필요성을 증대시켰으며 이는 에너지 과소비적 도시공간구조를 가져왔다.

• 산업경영시스템학회지
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• 제47권1호
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• pp.41-50
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• 2024

Korea is facing a significant problem with historically low fertility rates, which is becoming a major social issue affecting the economy, labor force, and national security. This study analyzes the factors contributing to the regional gap in fertility rates and derives policy implications. The government and local authorities are implementing a range of policies to address the issue of low fertility. To establish an effective strategy, it is essential to identify the primary factors that contribute to regional disparities. This study identifies these factors and explores policy implications through machine learning and explainable artificial intelligence. The study also examines the influence of media and public opinion on childbirth in Korea by incorporating news and online community sentiment, as well as sentiment fear indices, as independent variables. To establish the relationship between regional fertility rates and factors, the study employs four machine learning models: multiple linear regression, XGBoost, Random Forest, and Support Vector Regression. Support Vector Regression, XGBoost, and Random Forest significantly outperform linear regression, highlighting the importance of machine learning models in explaining non-linear relationships with numerous variables. A factor analysis using SHAP is then conducted. The unemployment rate, Regional Gross Domestic Product per Capita, Women's Participation in Economic Activities, Number of Crimes Committed, Average Age of First Marriage, and Private Education Expenses significantly impact regional fertility rates. However, the degree of impact of the factors affecting fertility may vary by region, suggesting the need for policies tailored to the characteristics of each region, not just an overall ranking of factors.

• 아태비즈니스연구
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• 제14권4호
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• pp.233-254
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• 2023

Purpose - This study aims to verify whether the effect of tax avoidance on corporate value is non-linear in the Korean financial markets. Design/methodology/approach - This study believes that the cause of the inconsistent empirical analysis results of previous studies that verified the relationship between tax avoidance and firm value may be an error in assuming linearity, and verifies whether a nonlinear relationship exists. The sample company in this study is a December settlement corporation listed on the Korean stock market, and the analysis period is from 2000 to 2021. In the empirical analysis model, Tobin's Q is used as a proxy for corporate value, tax avoidance is used as the main independent variable, and a regression model is designed with corporate size, growth rate, and debt ratio set as control variables. Findings - As a result of the empirical analysis, it can be confirmed that there is an inverted U-shaped nonlinear relationship between tax avoidance and corporate value. In the additional analysis using Ohlson (1995) firm valuation model for the robustness of the results of the empirical analysis, the same nonlinear value relationship between tax avoidance can be confirmed. Research implications or Originality - This study is considered to be meaningful in that it verifies the non-linear relationship of tax avoidance, which has not been attempted in previous studies. The meaning of the inverted U-shaped nonlinear relationship presented in this study is that corporate tax avoidance acts as a factor that increases corporate value up to a certain level, but rather becomes a factor that decreases corporate value when it exceeds a critical point. These results are expected to provide new perspectives and perspectives on tax avoidance to companies belonging to the Korean capital market.

• 한국신재생에너지학회:학술대회논문집
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• 한국신재생에너지학회 2005년도 춘계학술대회
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• pp.335-338
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• 2005

Starting with the development of environmentally friendly electric controlled engine, sensors have played an increasing role in automotive technology. Electric power steering (EPS) systems are more and more replacing hydraulic systems. To improve fuel economy, the power assistance is provided by an electric drive. In this paper, development of a unique torque sensor for EPS is introduced. A capacitive type torque sensor is concluded to be suitable for EPS because its output is accurate, linear and robust against the variance of temperature, and patents have not applied so much.