• Title/Summary/Keyword: Model and algorithm development

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Improving the Genetic Algorithm for Maximizing Groundwater Development During Seasonal Drought

  • Chang, Sun Woo;Kim, Jitae;Chung, Il-Moon;Lee, Jeong Eun
    • The Journal of Engineering Geology
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    • v.30 no.4
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    • pp.435-446
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    • 2020
  • The use of groundwater in Korea has increased in recent years to the point where its extraction is restricted in times of drought. This work models the groundwater pumping field as a confined aquifer in a simplified simulation of groundwater flow. It proposes a genetic algorithm to maximize groundwater development using a conceptual model of a steady-state confined aquifer. Solving the groundwater flow equation numerically calculates the hydraulic head along the domain of the problem; the algorithm subsequently offers optimized pumping strategies. The algorithm proposed here is designed to improve a prior initial groundwater management model. The best solution is obtained after 200 iterations. The results compare the computing time for five simulation cases. This study shows that the proposed algorithm can facilitate better groundwater development compared with a basic genetic algorithm.

Pavement Performance Model Development Using Bayesian Algorithm (베이지안 기법을 활용한 공용성 모델개발 연구)

  • Mun, Sungho
    • International Journal of Highway Engineering
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    • v.18 no.1
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    • pp.91-97
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    • 2016
  • PURPOSES : The objective of this paper is to develop a pavement performance model based on the Bayesian algorithm, and compare the measured and predicted performance data. METHODS : In this paper, several pavement types such as SMA (stone mastic asphalt), PSMA (polymer-modified stone mastic asphalt), PMA (polymer-modified asphalt), SBS (styrene-butadiene-styrene) modified asphalt, and DGA (dense-graded asphalt) are modeled in terms of the performance evaluation of pavement structures, using the Bayesian algorithm. RESULTS : From case studies related to the performance model development, the statistical parameters of the mean value and standard deviation can be obtained through the Bayesian algorithm, using the initial performance data of two different pavement cases. Furthermore, an accurate performance model can be developed, based on the comparison between the measured and predicted performance data. CONCLUSIONS : Based on the results of the case studies, it is concluded that the determined coefficients of the nonlinear performance models can be used to accurately predict the long-term performance behaviors of DGA and modified asphalt concrete pavements. In addition, the developed models were evaluated through comparison studies between the initial measurement and prediction data, as well as between the final measurement and prediction data. In the model development, the initial measured data were used.

Development of a teaching-learning model for effective algorithm education (효과적인 알고리즘 교육을 위한 교수-학습 모형 개발)

  • Han, Oak-Young;Kim, Jae-Hyoun
    • The Journal of Korean Association of Computer Education
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    • v.14 no.2
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    • pp.13-22
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    • 2011
  • The importance of algorithm education has been emphasized for creative problem-solving capability. Especially, algorithm teaching materials related with mathematics and science are under development to enhance logical thinking. However, there are not enough teaching-learning models applicable in the field of education. Therefore, this paper proposed a teaching-learning model for effective algorithm education. The teaching-learning model reflects two characteristics : an algorithm learning process is spiral, and algorithm education is based on logical thinking. Furthermore, a survey was conducted for students' satisfaction, and the result was a mixed teaching-learning model with PBL, SDL, and peer tutoring. Based on the proposed model, examples of classes for mathematics and science are suggested to show the feasibility of effective algorithm education.

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Design of Fuzzy IMM Algorithm based on Basis Sub-models and Time-varying Mode Transition Probabilities

  • Kim Hyun-Sik;Chun Seung-Yong
    • International Journal of Control, Automation, and Systems
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    • v.4 no.5
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    • pp.559-566
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    • 2006
  • In the real system application, the interacting multiple model (IMM) based algorithm requires less computing resources as well as a good performance with respect to the various target maneuverings. And it further requires an easy design procedure in terms of its structures and parameters. To solve these problems, a fuzzy interacting multiple model (FIMM) algorithm, which is based on the basis sub-models defined by considering the maneuvering property and the time-varying mode transition probabilities designed by using the mode probabilities as inputs of a fuzzy decision maker, is proposed. To verify the performance of the proposed algorithm, airborne target tracking is performed. Simulation results show that the FIMM algorithm solves all problems in the real system application of the IMM based algorithm.

이송물체의 질량 측정 속도 및 정밀도 향상 모사 연구

  • 이우갑;정진완;김광표
    • Proceedings of the Korean Society of Precision Engineering Conference
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    • 1992.10a
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    • pp.161-165
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    • 1992
  • The important properties of industrial scale or weighing machine operated in production lines are quickness and precision. This paper presents an algorithm which meets the importance. The algorithm of Recursive Least Squares Regression is described for the weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm is illustrated in digital simulation. Discussions have been extended to the development of fast converging algorithm. It turns out that the algorithm shows several desirable features suitable for microcomputer assisted realtime signal processing.

Development of Speed and Precision in the Mass Measurement of Moving Object (이송 물체의 질령 측정 속도 및 정밀도 향상 모사 연구)

  • Lee, Woo Gab;Chung, Jin Wan;Kim, Kwang Pyo
    • Journal of the Korean Society for Precision Engineering
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    • v.11 no.6
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    • pp.136-142
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    • 1994
  • This study presents an algorithm and related techniques which could satisfy the important properties of check weighers and conveyor scales. The algorithm of Recursive Least Squares Regression is described for te weighing system simulated as a dynamic model of the second order. Using the model and the algorithm, model parameters and then the mass being weighed can be determined from the step input. The performance of the algorithm is illustrated in digital simulation. Discussions are extended to the development of fast converging algorithm. It turns out that the algorithm shows several desirable features suitable for microcomputer assisted real-time signal processing, which are high precision and stability in noisy environment.

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The NCF Algorithm for the Control of an Electro-mechanical Active Suspension System (전기-기계식 능동 현가장치 제어를 위한 NCF 알고리즘)

  • Han, In-Sik;Lee, Yoon-Bok;Choi, Kyo-Jun;Kim, Jae-Yong;Jang, Myeong-Eon
    • Transactions of the Korean Society of Automotive Engineers
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    • v.20 no.4
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    • pp.1-9
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    • 2012
  • The NCF control algorithm for an active suspension system was proposed and investigated. The NCF algorithm using spring dynamic variation force and suspension relative velocity was applied to the 1/4 vehicle model and numerical analysis was performed. Vehicle's performances such as vehicle displacement, vehicle acceleration, suspension deflection, tire deflection and absorbed power were calculated and compared with those of the passive, semi-active and LQR active suspension system that use full state feedback. Numerical results show that the proposed NCF active suspension system has superior performance compared with the passive and semi-active suspension system and has very similar performance compared with the LQR active suspension system. So the proposed NCF algorithm is considered as a highly practical algorithm because it requires only one displacement sensor in a 1/4 vehicle model.

Real time optimization of fed-batch culture of recombinant yeast

  • Na, Jeong-Geol;Kim, Hyeon-Han;Jang, Yong-Geun;Jeong, Bong-Hyeon
    • 한국생물공학회:학술대회논문집
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    • 2001.11a
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    • pp.81-84
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    • 2001
  • A real time optimization algorithm for fed-batch cultures of recombinant yeast to determine the optimal substrate feed rate profile has been developed. Its development involved four key steps: (1) development of reliable adaptive model. (2) development of optimization algorithm. (3) design of on-line model update algorithm to be incorporated into the optimization algorithm and (4) experimental validation. A recombinant Saccharomyces cerevisiae producing human parathyroid hormone (hPTH) was chosen as the model strain. It was found to be very successful in maintaining cell growth and galactose consumption at leigh levels, thus resulting in significant improvements in the productivity (up to 2.1 times) and intact hPTH concentration (up to 1.5 times) compared with the case of an intermittent glucose and galactose, or galactose feeding.

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Development of Big Data-based Cardiovascular Disease Prediction Analysis Algorithm

  • Kyung-A KIM;Dong-Hun HAN;Myung-Ae CHUNG
    • Korean Journal of Artificial Intelligence
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    • v.11 no.3
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    • pp.29-34
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    • 2023
  • Recently, the rapid development of artificial intelligence technology, many studies are being conducted to predict the risk of heart disease in order to lower the mortality rate of cardiovascular diseases worldwide. This study presents exercise or dietary improvement contents in the form of a software app or web to patients with cardiovascular disease, and cardiovascular disease through digital devices such as mobile phones and PCs. LR, LDA, SVM, XGBoost for the purpose of developing "Life style Improvement Contents (Digital Therapy)" for cardiovascular disease care to help with management or treatment We compared and analyzed cardiovascular disease prediction models using machine learning algorithms. Research Results XGBoost. The algorithm model showed the best predictive model performance with overall accuracy of 80% before and after. Overall, accuracy was 80.0%, F1 Score was 0.77~0.79, and ROC-AUC was 80%~84%, resulting in predictive model performance. Therefore, it was found that the algorithm used in this study can be used as a reference model necessary to verify the validity and accuracy of cardiovascular disease prediction. A cardiovascular disease prediction analysis algorithm that can enter accurate biometric data collected in future clinical trials, add lifestyle management (exercise, eating habits, etc.) elements, and verify the effect and efficacy on cardiovascular-related bio-signals and disease risk. development, ultimately suggesting that it is possible to develop lifestyle improvement contents (Digital Therapy).

A Study on Fuzzy Interacting Multiple Model Algorithm for Maneuvering Target Tracking (기동 표적 추적을 위한 퍼지 IMM 알고리즘에 관한 연구)

  • Kim Hyun-Sik;Kim Jin-Soek;Hwang Soo-Bok
    • Journal of the Korea Institute of Military Science and Technology
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    • v.7 no.4 s.19
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    • pp.5-12
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    • 2004
  • The tracking algorithm based on the interacting multiple model(IMM) requires a considerable number of sub-models for the various maneuvering targets in order to have a good performance. But it is not feasible to use the nm algorithm in the real system because of the computational burden. Therefore, we need an algorithm which requires less computing resources while maintaining a good performance. In this paper, we propose a fuzzy interacting multiple model algorithm(FIMMA) for the tracking of maneuvering targets, which uses a minimal number of sub-models by considering the maneuvering properties and adjusts the mode transition probabilities by using the mode probability as a fuzzy input. In order to verify the performance of FIMMA, the developed algorithm is applied to the tracking of i borne targets. Simulation results show that the FIMMA is very effective in the tracking of maneuvering targets.