• Journal of Biosystems Engineering
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• 제24권5호
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• pp.445-452
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• 1999

This study was conducted to develop a searching algorithm for optimal daily temperature setpoint greenhouse. An algorithm using crop growth and energy models was developed to determine optimum crop growth environment. The results of this study were as follows: 1. Mathematical models for crop growth and energy consumption were derived to define optimal daily temperature setpoint. 2. Optimum temperature setpoint, which could maximize performance criterion, was determined by using Pontryagin maximum principle. 3. Dynamic control of daily temperature using the developed algorithm showed higher performance criterion than static control with fixed temperature setpoint. Performance criteria for dynamic control models were with simulated periodic weather data and with real weather data, increased by 48% and 60%, respectively.

• 대한기계학회논문집B
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• 제22권7호
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• pp.905-914
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• 1998

View factor determination is very important in thermal analysis problems with surface radiation but it is very difficult to determine view factors for complex geometries. Exact calculation of view factors for crystal growth furnace is essential due to not only its high surface temperature but the radiation shield, complicated heating system. In this study, view factor calculation algorithm is introduced and applied to cylindrical crystal growth furnace. This algorithm is based on the Hemi-Cube Algorithm and the results obtained with this algorithm show good agreements with those of analytical solution. As an application of this algorithm, temperature profiles and heating value distributions for various furnaces are calculated and the shape criteria for better furnace are suggested.

• ETRI Journal
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• 제31권2호
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• pp.240-242
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• 2009

A computationally efficient implementation of the progressive edge-growth algorithm is presented. This implementation uses an array of red-black (RB) trees to manage the layered structure of check nodes and adopts a new strategy to expand the Tanner graph. The complexity analysis and the simulation results show that the proposed approach reduces the computational effort effectively. In constructing a low-density parity check code with a length of $10^4$, the RB-tree-array-based implementation takes no more 10% of the time required by the original method.

• 디지털융복합연구
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• 제15권6호
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• pp.229-236
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• 2017

효율적인 빈발 패턴 알고리즘은 연관 규칙 마이닝이나 융복합을 위한 마이닝 과정에서 필수적인 요소이며 많은 활용성을 가지고 있다. 패턴 마이닝을 위한 많은 모델들이 빈발 패턴에 관한 정보를 추출하여 FP-트리를 이용하여 저장하고 있다. 본 논문에서는 항목들의 무게중심을 이용한 새로운 빈발 패턴 알고리즘(CAWFP-Growth)을 제안하여 항목들이 가지는 가중치와 빈도수를 같이 고려하여 항목간의 중심을 계산하여 기존의 FP-Growth 알고리즘의 효율성을 향상시킨다. 제안한 방법은 하향 폐쇄의 성질을 유지하기 위한 기존의 전역적 최대치 가중치 지지도를 필요로 하지 않기 때문에 자연히 빈발 패턴의 탐색시간이 줄어들고 정보의 손실을 줄일 수 있다. 실험결과를 통하여 제안된 알고리즘이 기존의 동적가중치를 이용하는 다른 방법과 비교해볼 때, 항목들의 무게중심이 빈발패턴의 정확한 정보를 유지하고 FP-트리의 처리시간을 줄여주기 때문에 제안한 방법의 중요성을 보이고 있다 또한 가상 분산모드에서 맵리듀스 프레임을 기반으로 빅데이터를 모델링하고 향후 완전분산 모드에서 제안한 알고리즘의 모델링이 필요하다.

• 한국지능시스템학회논문지
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• 제13권5호
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• pp.621-626
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• 2003

In this paper, we modeled a virtual life (VL) that reacts to the user s action according to its own behavioral characteristics and grows itself. We established some conditions with which such a VL is designed. Genetic Algorithm is used for the growth process that changes the VL s properties. In this process, the parameter values of the VL s properties are encoded as one chromosome, and the GA operations change this chromosome. The VL s reaction to the user s action is determined by these properties as well as the general expectation of each reaction. These properties are evaluated through 5 fitness measures so as to deal with multi-objective criteria. Here, we present the simulation of the growth Process, and show some experimental results.

• 한국정보과학회논문지:시스템및이론
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• 제29권11호
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• pp.634-639
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• 2002

최단 경로 탐색 알고리즘 (Shortest Path Algorithm)은 출발지에서 목적지에 이르는 여러 경로 중에서 가장 경제적이고 효율적인 경로를 찾는 알고리즘으로 레이블링 기법에 기초하고 있다. 레이블링 기법에는 레이블 고정(Label-Setting) 기법과 레이블 수정 (Label-Correcting) 기법이 있다. One-to-One 최단 경로 탐색 알고리즘에서 레이블 고정 기법이 빠르다고 알려져 왔으나 최근 연구에서 대용량 도로 데이터에 대한 실험을 통해 레이블 수정이 레이블 고정보다 탐색 씨간이 빠름을 보였다[1,2]. 레이블 수정 기법 중에서 가장 속도가 빠른 것은 그래프 성장 (Graph Growth) 알고리즘인데, 이 알고리즘은 One-to-All 방식을 사용하고 있으므로 One-to-One 최단 경로 탐색에는 적합하지 않다. 본 논문에서는 One-to-One 방식을 사용하는 새로운 알고리즘을 제안하였고, 실험결과 그래프 성장 알고리즘의 성능에 비해 새로 제안된 알고리즘의 성능이 30~40 향상되었음을 알 수 있었다.

• 대한원격탐사학회:학술대회논문집
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• 대한원격탐사학회 2007년도 Proceedings of ISRS 2007
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• pp.329-332
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• 2007

Annual vegetation growth patterns are determined by the intrinsic phenological characteristics of each land cover types. So, if typical growth patterns of each land cover types are well-estimated, and a NDVI time-series data of a certain area is compared to those estimated patterns, we can implement more advanced analyses such as a land surface-type classification or a land surface type change detection. In this study, we utilized Terra MODIS NDVI 250m data and compressed full annual NDVI time series data into several indices using the Harmonic Analysis of Time Series(HANTS) algorithm which extracts the most significant frequencies expected to be presented in the original NDVI time-series data. Then, we found these frequencies patterns, described by amplitude and phase data, were significantly different from each other according to vegetation types and these could be used for land cover classification. However, in spite of the capabilities of the HANTS algorithm for detecting and interpolating cloud-contaminated NDVI values, some distorted NDVI pixels of June, July and August, as well as the long rainy season in Korea, are not properly corrected. In particular, in the case of two or three successive NDVI time-series data, which are severely affected by clouds, the HANTS algorithm outputted wrong results.

• Journal of Communications and Networks
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• 제17권4호
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• pp.346-350
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• 2015

It is known that the progressive edge-growth (PEG) algorithm can be used to construct low-density parity-check (LDPC) codes at finite code lengths with large girths through the establishment of edges between variable and check nodes in an edge-by-edge manner. In [1], the authors derived a class of LDPC codes for relay communication systems by extending the full-diversity root-LDPC code. However, the submatrices of the parity-check matrix H corresponding to this code were constructed separately; thus, the girth of H was not optimized. To solve this problem, this paper proposes a modified PEG algorithm for use in the design of large girth and full-diversity LDPC codes. Simulation results indicated that the LDPC codes constructed using the modified PEG algorithm exhibited a more favorable frame error rate performance than did codes proposed in [1] over block-fading channels.

• 생물환경조절학회지
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• 제2권1호
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• pp.27-36
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• 1993

Carbon dioxide enrichment for greenhouse crops has generally been a standard commercial practice for many years. Vegetable crops such as tomato, cucumber, and lettuce respond positively to the $CO_2$ enrichment. But improper $CO_2$ enrichment leads to physiological damage and economical loss. This study was carried out to develop a $CO_2$ concentration control algorithm considering growth stage and efficiency. The measurand was $CO_2$ consumption rate and top fresh weight that represents growth stage. The weight of top fresh lettuce as a whole in the tray was measured through a non-destructive method. The demand in $CO_2$ concentration according to growth stage was investigated. The results are summarized as follows. 1. The $CO_2$ consumption rate could be measured within the error of $\pm$ 15.4mg$CO_2$/hr in the range of $CO_2$ concentration of 500-1500ppm. 2. The weight of top fresh lettuce could be measured within the error $\pm$ 4.3g in the range of 0-1400g. 3. The $CO_2$ control model developed could determine an economical $CO_2$ supply rate considering $CO_2$ consumption rate and leakage rate. 4. The $CO_2$ control algorithm based on the control model was composed of feedforward control for maintaining a stable $CO_2$ concentration level, and feedback control with $CO_2$ consumption rate and top fresh weight for adapting to the change in $CO_2$ demand by growth stage. 5. For the performance test with the developed control algorithm on lettuce the decrease in $CO_2$ supply rate was obtained without a significant decrease in top fresh weight.

• International Journal of Computer Science & Network Security
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• 제21권1호
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• pp.220-225
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• 2021

Human population growth rate is an important parameter for real-world planning. Common approaches rely upon fixed parameters like human population, mortality rate, fertility rate, which is collected historically to determine the region's population growth rate. Literature does not provide a solution for areas with no historical knowledge. In such areas, machine learning can solve the problem, but a multitude of machine learning algorithm makes it difficult to determine the best approach. Further, the missing feature is a common real-world problem. Thus, it is essential to compare and select the machine learning techniques which provide the best and most robust in the presence of missing features. This study compares 17 machine learning techniques (base learners and ensemble learners) performance in predicting the human population growth rate of the country. Among the 17 machine learning techniques, random forest outperformed all the other techniques both in predictive performance and robustness towards missing features. Thus, the study successfully demonstrates and compares machine learning techniques to predict the human population growth rate in settings where historical data and feature information is not available. Further, the study provides the best machine learning algorithm for performing population growth rate prediction.