Lee, Sang Hoon;Huh, Jin Wook;Kang, Sincheon;Lee, Myung Chun
Journal of the Korea Institute of Military Science and Technology
/
v.15
no.6
/
pp.721-728
/
2012
The tracked SUGVs(Small Unmanned Ground Vehicles) are frequently operated in the narrow slope such as stairs and trails. But due to the nature of the tracked vehicle which is steered using friction between the track and the ground and the limited field of view of driving cameras mounted on the lower position, it is not easy for SUGVs to trace narrow slopes. To properly trace inclined narrows, it is very important for SUGVs to keep it's heading direction to the slope. As a matter of factor, no roll value control of a SUGV can makes it's heading being located in the direction of the slope in general terrains. But, the problem is that we cannot directly control roll motion for SUGV. Instead we can control yaw motion. In this paper, a new slope driving method that enables the vehicle trace the narrow slopes with IMU sensor usually mounted in the SUGV is suggested which including an estimation technique of the desired yaw angle corresponding to zero roll angle. In addition, a fuzzy steering controller robust to changes in driving speed and the stair geometry is designed to simulate narrow slope driving with the suggested method. It is shown that the suggested method is quite effective through the simulation.
Studying slope stability is an important branch of civil engineering. In this way, engineers have employed machine learning models, due to their high efficiency in complex calculations. This paper examines the robustness of various novel optimization schemes, namely equilibrium optimizer (EO), Harris hawks optimization (HHO), water cycle algorithm (WCA), biogeography-based optimization (BBO), dragonfly algorithm (DA), grey wolf optimization (GWO), and teaching learning-based optimization (TLBO) for enhancing the performance of adaptive neuro-fuzzy inference system (ANFIS) in slope stability prediction. The hybrid models estimate the factor of safety (FS) of a cohesive soil-footing system. The role of these algorithms lies in finding the optimal parameters of the membership function in the fuzzy system. By examining the convergence proceeding of the proposed hybrids, the best population sizes are selected, and the corresponding results are compared to the typical ANFIS. Accuracy assessments via root mean square error, mean absolute error, mean absolute percentage error, and Pearson correlation coefficient showed that all models can reliably understand and reproduce the FS behavior. Moreover, applying the WCA, EO, GWO, and TLBO resulted in reducing both learning and prediction error of the ANFIS. Also, an efficiency comparison demonstrated the WCA-ANFIS as the most accurate hybrid, while the GWO-ANFIS was the fastest promising model. Overall, the findings of this research professed the suitability of improved intelligent models for practical slope stability evaluations.
Recently, Global network expansion strategy of GTOs(Global Terminal Operator) coupled with each country's port policy, plays huge role for the evolution of modern container port. The Chinese ports can be regarded as the major markets to the GTOs. However, there are scant of researches for finding the key success factors of GTOs' strategies when they consider to invest in overseas. In this respect, the aims of this study were to draw out the evaluation variables for successful investment strategies of GTOs, and to calculate the selected target ports. The 14 variables are selected including the variable named 'development potentiality of a port' through literature reviews. Using the Factor Analysis (FA) based on selected variables, four principal factors were extracted such as 'ability for port operating and cargo generating', 'the trade route and volume', 'the calling potentiality for large vessels' and 'the possibility of utilization of existing infrastructure'. In addition, the weights of factors and variables are evaluated through Fuzzy AHP method. As a result, 'ability for port operating and cargo generating' is chosen as the most important factor among principal factors as scored 0.343, and 'the development potentiality of a port' (0.107) is represented as the most important variable among 14 detailed variables. In overall, from the Global Terminal Operator's point of view, Shanghai is ranked as most suitable port for operating new terminal among the top 5 Chinese ports.
Regional rainfall quantile depends on the identification of hydrologically homogeneous regions. Various variables relevant to precipitation can be used to form regions. Since the type and number of variables may lead to improve the efficiency of partitioning, it is important to select those precipitation related variables, which represent most of the information from all candidate variables. Multivariate analysis techniques can be used for this purpose. Procrustes analysis which can decrease the dimension of variables based on their correlations, are applied in this study. 42 rainfall related variables are decreased into 21 ones by Procrustes analysis. Factor analysis is applied to those selected variables and then 5 factors are extracted. Fuzzy-c means technique classifies 68 stations into 6 regions. As a result, the GEV distributions are fitted to 6 regions while the lognormal and generalized logistic distributions are fitted to 5 regions. For the comparison purpose with previous results, rainfall quantiles based on generalized logistic distribution are estimated by at-site frequency analysis, index flood method, and regional shape estimation method.
Inter-port competition is fiercer than in the past because of technological evolution in transport systems : the increasing side of containerships implies only a few calls in three or four ports at each end of the trade and the rest of the traffic being served by smaller feederships. It is therefore essential for big ports to be selected as one of these calls by the main shipowners, consortia and alliances to avoid rmarginalisation. In order to compete effectively, many ports have been obliged to modernise and extend considerably its existing ports or to build new port facilities. With the advent of major environmental legislation around the world, however, amenities such as fish and wildlife, clean air and water, access to the waterfront, and view protection took on greater importance. Ports are now being forced to incorporate environmental considerations into their planning and management functions in order to avoid additional costs or timing delays. The aim of this paper is to analyse the port value by which port comparison(or selection) will be made with HFP(Hierarchical Fuzzy Process) method. This was done by extracting and grouping the evaluation factors of port value by port experts : facility and location factor, logistics service factor environment and amenity factor, city and economic factor, and human and system factor. For empirical test of this method, 6 major ports in Northeast Asia were chosen and analysed. The order of importance for five evaluation factors were 1) facility and location factor 2) logistics service factor 3) human and system factor, 4) city and economic factor, and 5) environment and amenity factor. This means that geographical location and logistics services are still being considered as the most important factor to call the port by port users. even though environment and amenity factor shows relatively low figure. Among 6 major ports, Port of Kobe was ranked the first position in a comprehensive evaluation, while Ports of Busan and Kwangyang were 4th and 5th respectively. This implies that Port of Busan should make much efforts to enhance the existing facilities as well as management system.
Journal of the Korean Institute of Landscape Architecture
/
v.48
no.3
/
pp.22-33
/
2020
Sign system is one of the most widely used guide media in scenic spots. It plays vital role in introducing cultural values of destinations to tourists with better visit experience. The purpose of this study is to derive the influence factors of the sign system of Mount Tai scenic area for tourists, analyze the satisfaction of tourists, and provide suggestions for the sign system of Mount Tai Mountaineering Road to improve tourists' satisfaction in the future. The evaluation items of Mount Tai Mountaineering Road sign system were derived from the previous studies and then subdivided comprehensively. Survey by questionnaires was carried out to obtain the influence factors. In order to understand the satisfaction degree of tourists, fuzzy comprehensive evaluation was implemented. The research results of this study are summarized as follows. First, four influence factors of the sign system on Mountaineering Road of Mount Tai were concluded as the interpretation content, appearance modeling, interpretation methods and layout management. Second, the order of weight values of influence factors was the interpretation content, appearance modeling, interpretation methods and layout management respectively from high to low, which means that tourists paid more attention to practicality and aesthetics. Third, the satisfaction degree of the tourists on the sign system was different. The satisfaction level for the three factors (interpretation content, appearance modeling, layout management) was good, while the satisfaction for interpretation method was medium. The reason was that it failed to deepen the understanding of tourists on the natural and cultural values of Mount Tai Mountaineering Road. These results indicate great significance to provide theoretical basis for the later readjustment and design of the sign system and to improve the overall satisfaction of tourists on tourism experience.
Journal of the Korean Institute of Intelligent Systems
/
v.9
no.4
/
pp.420-425
/
1999
The maximum demand controller is an electrical equipment installed at the consumer side of power system
for monitoring the electrical energy consumed during every integrating period and preventing the target
maximum demand (MD) being exceeded by disconnecting sheddable loads. By avoiding the peak loads and
spreading the energy requirement the controller contributes to maximizing the utility factor of the generator
systems. It results in not only saving the energy but also reducing the budget for constructing the natural base
facilities by keeping thc number of generating plants ~ninimumT. he conventional MD controllers often bring
about the large number of control actions during the every inteyating period and/or undesirable loaddisconnecting
operations during the beginning stage of the integrating period. These make the users aviod the
MD controllers. In this paper. fuzzy control technique is used to get around the disadvantages of the
conventional MD control system. The proposed MD controller consists of the predictor module and the fuzzy
MD control module. The proposed forecasting method uses the SOFM neural network model, differently from
time series analysis, and thus it has inherent advantages of neural network such as parallel processing,
generalization and robustness. The MD fuzzy controller determines the sensitivity of control action based on
the time closed to the end of the integrating period and the urgency of the load interrupting action along the
predicted demand reaching the target. The experimental results show that the proposed method has more
accurate forecastinglcontrol performance than the previous methods.
Siwon Kim;Jaekyung Kwon;Jaeseong Hwang;Sangsoo Lee;Choul ki Lee
The Journal of The Korea Institute of Intelligent Transport Systems
/
v.22
no.1
/
pp.192-207
/
2023
Commercialization of level-4 (Lv.4) autonomous driving applications requires the definition of a safe road environment under which autonomous vehicles can operate safely. Thus, a risk assessment model is required to determine whether the operation of autonomous vehicles can provide safety to is sufficiently prepared for future real-life traffic problems. Although the risk factors of autonomous vehicles were selected and graded, the decision-making method was applied as qualitative data using a survey of experts in the field of autonomous driving due to the cause of the accident and difficulty in obtaining autonomous driving data. The fuzzy linguistic representation of decision-makers and the fuzzy analytic hierarchy process (AHP), which converts uncertainty into quantitative figures, were implemented to compensate for the AHP shortcomings of the multi-standard decision-making technique. Through the process of deriving the weights of the upper and lower attributes, the road alignment, which is a physical infrastructure, was analyzed as the most important risk factor in the operation risk of autonomous vehicles. In addition, the operation risk of autonomous vehicles was derived through the example of the risk of operating autonomous vehicles for the 5 areas to be evaluated.
Journal of the Korean Institute of Intelligent Systems
/
v.10
no.5
/
pp.487-496
/
2000
In this paper, the Multi-FNN(Fuzzy-Neural Networks) model is identified and optimized using HCM(Hard C-Means) clustering method and genetic algorithms. The proposed Multi-FNN is based on Yamakawa's FNN and uses simplified inference as fuzzy inference method and error back propagation algorithm as learning rules. We use a HCM clustering and Genetic Algorithms(GAs) to identify both the structure and the parameters of a Multi-FNN model. Here, HCM clustering method, which is carried out for the process data preprocessing of system modeling, is utilized to determine the structure of Multi-FNN according to the divisions of input-output space using I/O process data. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. The aggregate performance index stands for an aggregate objective function with a weighting factor to consider a mutual balance and dependency between approximation and predictive abilities. According to the selection and adjustment of a weighting factor of this aggregate abjective function which depends on the number of data and a certain degree of nonlinearity, we show that it is available and effective to design an optimal Multi-FNN model. To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.
Journal of the Korean Institute of Intelligent Systems
/
v.10
no.4
/
pp.343-350
/
2000
In this paper, we propose the Multi-FPNN(Fuzzy Polynomial Neural Networks) model based on FNN and PNN(Polyomial Neural Networks) for optimal system identifacation. Here FNN structure is designed using fuzzy input space divided by each separated input variable, and urilized both in order to get better output performace. Each node of PNN structure based on GMDH(Group Method of Data handing) method uses two types of high-order polynomials such as linearane and quadratic, and the input of that node uses three kinds of multi-variable inputs such as linear and quadratic, and the input of that node and Genetic Algorithms(GAs) to identify both the structure and the prepocessing of parameters of a Multi-FPNN model. Here, HCM clustering method, which is carried out for data preproessing of process system, is utilized to determine the structure method, which is carried out for data preprocessing of process system, is utilized to determance index with a weighting factor is used to according to the divisions of input-output space. A aggregate performance inddex with a wegihting factor is used to achieve a sound balance between approximation and generalization abilities of the model. According to the selection and adjustment of a weighting factor of this aggregate abjective function which it is acailable and effective to design to design and optimal Multi-FPNN model. The study is illustrated with the aid of two representative numerical examples and the aggregate performance index related to the approximation and generalization abilities of the model is evaluated and discussed.
본 웹사이트에 게시된 이메일 주소가 전자우편 수집 프로그램이나
그 밖의 기술적 장치를 이용하여 무단으로 수집되는 것을 거부하며,
이를 위반시 정보통신망법에 의해 형사 처벌됨을 유념하시기 바랍니다.
[게시일 2004년 10월 1일]
이용약관
제 1 장 총칙
제 1 조 (목적)
이 이용약관은 KoreaScience 홈페이지(이하 “당 사이트”)에서 제공하는 인터넷 서비스(이하 '서비스')의 가입조건 및 이용에 관한 제반 사항과 기타 필요한 사항을 구체적으로 규정함을 목적으로 합니다.
제 2 조 (용어의 정의)
① "이용자"라 함은 당 사이트에 접속하여 이 약관에 따라 당 사이트가 제공하는 서비스를 받는 회원 및 비회원을
말합니다.
② "회원"이라 함은 서비스를 이용하기 위하여 당 사이트에 개인정보를 제공하여 아이디(ID)와 비밀번호를 부여
받은 자를 말합니다.
③ "회원 아이디(ID)"라 함은 회원의 식별 및 서비스 이용을 위하여 자신이 선정한 문자 및 숫자의 조합을
말합니다.
④ "비밀번호(패스워드)"라 함은 회원이 자신의 비밀보호를 위하여 선정한 문자 및 숫자의 조합을 말합니다.
제 3 조 (이용약관의 효력 및 변경)
① 이 약관은 당 사이트에 게시하거나 기타의 방법으로 회원에게 공지함으로써 효력이 발생합니다.
② 당 사이트는 이 약관을 개정할 경우에 적용일자 및 개정사유를 명시하여 현행 약관과 함께 당 사이트의
초기화면에 그 적용일자 7일 이전부터 적용일자 전일까지 공지합니다. 다만, 회원에게 불리하게 약관내용을
변경하는 경우에는 최소한 30일 이상의 사전 유예기간을 두고 공지합니다. 이 경우 당 사이트는 개정 전
내용과 개정 후 내용을 명확하게 비교하여 이용자가 알기 쉽도록 표시합니다.
제 4 조(약관 외 준칙)
① 이 약관은 당 사이트가 제공하는 서비스에 관한 이용안내와 함께 적용됩니다.
② 이 약관에 명시되지 아니한 사항은 관계법령의 규정이 적용됩니다.
제 2 장 이용계약의 체결
제 5 조 (이용계약의 성립 등)
① 이용계약은 이용고객이 당 사이트가 정한 약관에 「동의합니다」를 선택하고, 당 사이트가 정한
온라인신청양식을 작성하여 서비스 이용을 신청한 후, 당 사이트가 이를 승낙함으로써 성립합니다.
② 제1항의 승낙은 당 사이트가 제공하는 과학기술정보검색, 맞춤정보, 서지정보 등 다른 서비스의 이용승낙을
포함합니다.
제 6 조 (회원가입)
서비스를 이용하고자 하는 고객은 당 사이트에서 정한 회원가입양식에 개인정보를 기재하여 가입을 하여야 합니다.
제 7 조 (개인정보의 보호 및 사용)
당 사이트는 관계법령이 정하는 바에 따라 회원 등록정보를 포함한 회원의 개인정보를 보호하기 위해 노력합니다. 회원 개인정보의 보호 및 사용에 대해서는 관련법령 및 당 사이트의 개인정보 보호정책이 적용됩니다.
제 8 조 (이용 신청의 승낙과 제한)
① 당 사이트는 제6조의 규정에 의한 이용신청고객에 대하여 서비스 이용을 승낙합니다.
② 당 사이트는 아래사항에 해당하는 경우에 대해서 승낙하지 아니 합니다.
- 이용계약 신청서의 내용을 허위로 기재한 경우
- 기타 규정한 제반사항을 위반하며 신청하는 경우
제 9 조 (회원 ID 부여 및 변경 등)
① 당 사이트는 이용고객에 대하여 약관에 정하는 바에 따라 자신이 선정한 회원 ID를 부여합니다.
② 회원 ID는 원칙적으로 변경이 불가하며 부득이한 사유로 인하여 변경 하고자 하는 경우에는 해당 ID를
해지하고 재가입해야 합니다.
③ 기타 회원 개인정보 관리 및 변경 등에 관한 사항은 서비스별 안내에 정하는 바에 의합니다.
제 3 장 계약 당사자의 의무
제 10 조 (KISTI의 의무)
① 당 사이트는 이용고객이 희망한 서비스 제공 개시일에 특별한 사정이 없는 한 서비스를 이용할 수 있도록
하여야 합니다.
② 당 사이트는 개인정보 보호를 위해 보안시스템을 구축하며 개인정보 보호정책을 공시하고 준수합니다.
③ 당 사이트는 회원으로부터 제기되는 의견이나 불만이 정당하다고 객관적으로 인정될 경우에는 적절한 절차를
거쳐 즉시 처리하여야 합니다. 다만, 즉시 처리가 곤란한 경우는 회원에게 그 사유와 처리일정을 통보하여야
합니다.
제 11 조 (회원의 의무)
① 이용자는 회원가입 신청 또는 회원정보 변경 시 실명으로 모든 사항을 사실에 근거하여 작성하여야 하며,
허위 또는 타인의 정보를 등록할 경우 일체의 권리를 주장할 수 없습니다.
② 당 사이트가 관계법령 및 개인정보 보호정책에 의거하여 그 책임을 지는 경우를 제외하고 회원에게 부여된
ID의 비밀번호 관리소홀, 부정사용에 의하여 발생하는 모든 결과에 대한 책임은 회원에게 있습니다.
③ 회원은 당 사이트 및 제 3자의 지적 재산권을 침해해서는 안 됩니다.
제 4 장 서비스의 이용
제 12 조 (서비스 이용 시간)
① 서비스 이용은 당 사이트의 업무상 또는 기술상 특별한 지장이 없는 한 연중무휴, 1일 24시간 운영을
원칙으로 합니다. 단, 당 사이트는 시스템 정기점검, 증설 및 교체를 위해 당 사이트가 정한 날이나 시간에
서비스를 일시 중단할 수 있으며, 예정되어 있는 작업으로 인한 서비스 일시중단은 당 사이트 홈페이지를
통해 사전에 공지합니다.
② 당 사이트는 서비스를 특정범위로 분할하여 각 범위별로 이용가능시간을 별도로 지정할 수 있습니다. 다만
이 경우 그 내용을 공지합니다.
제 13 조 (홈페이지 저작권)
① NDSL에서 제공하는 모든 저작물의 저작권은 원저작자에게 있으며, KISTI는 복제/배포/전송권을 확보하고
있습니다.
② NDSL에서 제공하는 콘텐츠를 상업적 및 기타 영리목적으로 복제/배포/전송할 경우 사전에 KISTI의 허락을
받아야 합니다.
③ NDSL에서 제공하는 콘텐츠를 보도, 비평, 교육, 연구 등을 위하여 정당한 범위 안에서 공정한 관행에
합치되게 인용할 수 있습니다.
④ NDSL에서 제공하는 콘텐츠를 무단 복제, 전송, 배포 기타 저작권법에 위반되는 방법으로 이용할 경우
저작권법 제136조에 따라 5년 이하의 징역 또는 5천만 원 이하의 벌금에 처해질 수 있습니다.
제 14 조 (유료서비스)
① 당 사이트 및 협력기관이 정한 유료서비스(원문복사 등)는 별도로 정해진 바에 따르며, 변경사항은 시행 전에
당 사이트 홈페이지를 통하여 회원에게 공지합니다.
② 유료서비스를 이용하려는 회원은 정해진 요금체계에 따라 요금을 납부해야 합니다.
제 5 장 계약 해지 및 이용 제한
제 15 조 (계약 해지)
회원이 이용계약을 해지하고자 하는 때에는 [가입해지] 메뉴를 이용해 직접 해지해야 합니다.
제 16 조 (서비스 이용제한)
① 당 사이트는 회원이 서비스 이용내용에 있어서 본 약관 제 11조 내용을 위반하거나, 다음 각 호에 해당하는
경우 서비스 이용을 제한할 수 있습니다.
- 2년 이상 서비스를 이용한 적이 없는 경우
- 기타 정상적인 서비스 운영에 방해가 될 경우
② 상기 이용제한 규정에 따라 서비스를 이용하는 회원에게 서비스 이용에 대하여 별도 공지 없이 서비스 이용의
일시정지, 이용계약 해지 할 수 있습니다.
제 17 조 (전자우편주소 수집 금지)
회원은 전자우편주소 추출기 등을 이용하여 전자우편주소를 수집 또는 제3자에게 제공할 수 없습니다.
제 6 장 손해배상 및 기타사항
제 18 조 (손해배상)
당 사이트는 무료로 제공되는 서비스와 관련하여 회원에게 어떠한 손해가 발생하더라도 당 사이트가 고의 또는 과실로 인한 손해발생을 제외하고는 이에 대하여 책임을 부담하지 아니합니다.
제 19 조 (관할 법원)
서비스 이용으로 발생한 분쟁에 대해 소송이 제기되는 경우 민사 소송법상의 관할 법원에 제기합니다.
[부 칙]
1. (시행일) 이 약관은 2016년 9월 5일부터 적용되며, 종전 약관은 본 약관으로 대체되며, 개정된 약관의 적용일 이전 가입자도 개정된 약관의 적용을 받습니다.