• 한국연소학회:학술대회논문집
• /
• 2014.11a
• /
• pp.19-20
• /
• 2014

Boiler design should be desinged to maximize thermal efficiency of the system under imposed load requirement and a boiler should be validated for transient operation. If a proper prediction is possible on the transient behavior and transient characteristics of a boiler, one may asses the performance of boiler component, control logics and operation procedures. In this work, dynamic modeling method of boiler is presented and dynamic simulation of load runback scenario was carried out on suprecritical oil-firing boiler.

• Computers and Concrete
• /
• v.6 no.2
• /
• pp.155-165
• /
• 2009

Splitting tensile strength (STS) of high-performance concrete (HPC) is one of the important mechanical properties for structural design. This property is related to compressive strength (CS), water/binder (W/B) ratio and concrete age. This paper presents a clustering-based fuzzy model for the prediction of STS based on the CS and (W/B) at a fixed age (28 days). The data driven fuzzy model consists of three main steps: fuzzy clustering, inference system, and prediction. The system can be analyzed directly by the model from measured data. The performance evaluations showed that the fuzzy model is more accurate than the other prediction models concerned.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 1994.10a
• /
• pp.953-957
• /
• 1994

A performance prediction method is presented in this paper for design of a rotating machinery having power split/circulated transmisson with slip elements and planetary gears. And internal power flow patterns of such systems are theoretically analyzed by using mathematical modeling. To estimate usefulness of the designed machinary, geometrical approach has been adopted through the performance locus diagram which represents overall characteristics of the system. This gives us complect prediction of the qualitative performane and effects of design factors such as system layout, types and gear ratios of planetary gears and disign parameters of slip elements. The results for one of them are compared with experimental ones using dynamometer for verification.

• Journal of the Korean Society for Geothermal and Hydrothermal Energy
• /
• v.16 no.1
• /
• pp.17-25
• /
• 2020

Ground-coupled heat pump (GCHP) systems have become an efficient alternative to conventional cooling and heating methods due to their higher energy using efficiency. Although some experimental and simulation works related to performance analysis of GCHP systems for commercial buildings have been done, relatively little has been reported on the performance evaluation of GCHP systems for school buildings. The purpose of this simulation study is to evaluate the performance of a hypothetical GCHP system for a school building in Seoul. We collected various data of building specifications and construction materials for the building and then modeled to calculate hourly building loads with SketchuUp and TRNSYS V17. In addition, we used GLD (Ground Loop Design) V2016, a GCHP system design and simulation software, to design the GCHP system for the building and to simulate temperature of circulating water in ground heat exchanger. The variation of entering source temperature (EST) into the system was calculated with different prediction time and then each result was compared. For 20 years of prediction time, EST for baseline design (Case A) based on the hourly simulation results were outranged from the design criteria.

• Journal of information and communication convergence engineering
• /
• v.5 no.4
• /
• pp.339-345
• /
• 2007

Video transcoding is a technique used to convert a compressed input video stream with an arbitrary format, size, and bitrate into a different attribute video stream different attributes to provide a efficient video streaming service for the customers is dispersed in the heterogeneous networks. Specifically, frames deletion occur in a transcoding scheme that exploits the adjustment of frame rate, and at this time, the loss in temporal relation among frames due to frame deletion is compensated for the prediction of motion estimation by reusing motion vectors in the would-be deleted frames. But the processing time for transcoding don't have an improvement as much as our expectation because transcoding is done only within the transcoder. So in this paper, we propose a new transcoding algorithm based on prediction period to improve transcoding-related processing time. For this, we also modify the existing encoder so as to adjust dynamically frame rate based on the prediction period and deletion period of frames. To check how the proposed algorithm works nicely, we implement a video streaming system with the new transcoder and encoder to which it is applied. The result of the performance test shows that the streaming system with proposed algorithm improve 60% above in processing time and also PSNR have a good performance while the quality of pictures is preserved.

• Agribusiness and Information Management
• /
• v.6 no.2
• /
• pp.32-39
• /
• 2014

The goal of this research was to develop a portable system that could be used to evaluate the quality of milk in real time at a raw milk production site. A real-time portable quality evaluation system for raw milk was developed to enable non-destructive quality evaluation of somatic cell count (SCC), fat, protein, lactose, and total solid (TS) in milk samples. A prediction model of SCC, fat, protein, lactose, and TS was constructed using partial least squares (PLS) and 200 milk samples were used to evaluate the prediction performance of the portable quality evaluation system and high performance spectroscopy. Through prediction model development and verification, it was found that the accuracy of high performance spectroscopy was 90% for SSC, 96% for fat, 96% for protein, 91% for lactose, and 97% for TS. In comparison, the accuracy of the portable quality evaluation system was relatively low, at 90% for SSC, 95% for fat, 92% for protein, 89% for lactose, 92% for TS. However, the measurement time for high performance spectroscopy was 10 minutes for 1 sample, while for the portable quality evaluation system it was 6 minutes. This means that the high performance spectroscopy system can measure 48 samples per day (8 hours), while the portable quality evaluation system can measure 80 (8 hours). Therefore, it was found that the portable quality evaluation system enables quick on-site quality evaluation of milk samples.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.62 no.11
• /
• pp.1590-1597
• /
• 2013

Electric power is an important part in economic development. Moreover, an accurate load forecast can make a financing planning, power supply strategy and market research planned effectively. This paper used the fuzzy logic system to predict the regional electric power load. To design the fuzzy prediction system, the correlation-based clustering algorithm and TSK fuzzy model were used. Also, to improve the prediction system's capability, the moving average technique and relative increasing rate were used in the preprocessing procedure. Finally, using four regional electric power load in Taiwan, this paper verified the performance of the proposed system and demonstrated its effectiveness and usefulness.

• The KSFM Journal of Fluid Machinery
• /
• v.19 no.2
• /
• pp.27-35
• /
• 2016

The purpose of this study is to develop a method to predict the performance and economics of a micro gas turbine cogeneration system using performance correction curves. The variables of correction curves are ambient temperature, ambient pressure, relative humidity and load fraction. All of the values of correction factors were expressed as relative values with respect to design values at the ISO conditions. Once the correction curves are obtained, system performance can be predicted relatively easily compared to a detailed performance analysis method through a simple multiplication of the correction factors of various variables at any operating conditions. The predicted results using the correction curve method were compared with those by the detailed and more complex performance analysis in a wide operating range, and its feasibility was confirmed. To illustrate the usability of the correction curve method, the results of an economic analysis of a cogeneration system considering varying operating ambient condition and load was presented.

• The Journal of the Convergence on Culture Technology
• /
• v.10 no.4
• /
• pp.595-600
• /
• 2024

As the use of artificial intelligence technologies such as machine learning increases in research fields that predict learning outcomes or optimize learning pathways, the use of artificial intelligence in education is gradually making progress. This research is gradually evolving into more advanced artificial intelligence methods such as deep learning and reinforcement learning. This study aims to improve the method of predicting future learning performance based on the learner's past learning performance-history data. Therefore, to improve prediction performance, we propose conditional probability applying the Markov Chain method. This method is used to improve the prediction performance of the classifier by allowing the learner to add learning history data to the classification prediction in addition to classification prediction by machine learning. In order to confirm the effectiveness of the proposed method, a total of more than 30 experiments were conducted per algorithm and indicator using empirical data, 'Teaching aid-based early childhood education learning performance data'. As a result of the experiment, higher performance indicators were confirmed in cases using the proposed method than in cases where only the classification algorithm was used in all cases.

• KEPCO Journal on Electric Power and Energy
• /
• v.6 no.4
• /
• pp.413-418
• /
• 2020

It is necessary to manage the prediction accuracy of the machine learning model to prevent the decrease in the performance of the grid network condition prediction model due to overfitting of the initial training data and to continuously utilize the prediction model in the field by maintaining the prediction accuracy. In this paper, we propose an automation technique for maintaining the performance of the model, which increases the accuracy and reliability of the prediction model by considering the characteristics of the power grid state data that constantly changes due to various factors, and enables quality maintenance at a level applicable to the field. The proposed technique modeled a series of tasks for maintaining the performance of the power grid condition prediction model through the application of the workflow management technology in the form of a workflow, and then automated it to make the work more efficient. In addition, the reliability of the performance result is secured by evaluating the performance of the prediction model taking into account both the degree of change in the statistical characteristics of the data and the level of generalization of the prediction, which has not been attempted in the existing technology. Through this, the accuracy of the prediction model is maintained at a certain level, and further new development of predictive models with excellent performance is possible. As a result, the proposed technique not only solves the problem of performance degradation of the predictive model, but also improves the field utilization of the condition prediction model in a complex power grid system.