• Korean Management Science Review
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• v.29 no.1
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• pp.101-114
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• 2012

The demand for naval spare parts is intermittent and erratic. This feature, referred to as non-normal demand, makes forecasting difficult. Hierarchical forecasting using an aggregated time series can be more reliable to predict non-normal demand than direct forecasting. In practice the performance of hierarchical forecasting is not always superior to direct forecasting. The relative performance of the alternative forecasting methods depends on the demand features. This paper analyses the influence of the demand features on the performance of the alternative forecasting methods that use hierarchical and direct forecasting. Among various demand features variability, kurtosis, skewness and equipment groups are shown to significantly influence on the performance of the alternative forecasting methods.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.861-866
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• 2022

Seoul introduced the shared bicycle system, "Seoul Public Bike" in 2015 to help reduce traffic volume and air pollution. Hence, to solve various problems according to the supply and demand of the shared bicycle system, "Seoul Public Bike," several studies are being conducted. Most of the research is a strategic "Bicycle Rearrangement" in regard to the imbalance between supply and demand. Moreover, most of these studies predict demand by grouping features such as weather or season. In previous studies, demand was predicted by time-series-analysis. However, recently, studies that predict demand using deep learning or machine learning are emerging. In this paper, we can show that demand prediction can be made a little better by discovering new features or ordering the importance of various features based on well-known feature-patterns. In this study, by ordering the selection of new features or the importance of the features, a better coefficient of determination can be obtained even if the well-known deep learning or machine learning or time-series-analysis is exploited as it is. Therefore, we could be a better one for demand prediction.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.21 no.10
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• pp.553-558
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• 2009

Energy demand characteristics of hotel, hospital, and office building are compared to provide guidelines for combining building in community energy system design. The annual, monthly, and daily energy demand patterns for electricity, heating, hot water and cooling are qualitatively compared and important features are delineated based on the energy demand models. Key statistical values such as the mean, the maximum are also provided. Important features of the hourly demand patterns are summarized for weekdays and weekends. Substantial variations in both magnitudes and patterns are observed among the 3 building types and smart grouping or combination of building type and size is essential for a successive energy supply.

• Management Science and Financial Engineering
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• v.19 no.1
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• pp.1-10
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• 2013

Hierarchical forecasting strategy does not always outperform direct forecasting strategy. The performance generally depends on demand features. This research guides the use of the alternative forecasting strategies according to demand features. This paper developed and evaluated various classification models such as logistic regression (LR), artificial neural networks (ANN), decision trees (DT), boosted trees (BT), and random forests (RF) for predicting the relative performance of the alternative forecasting strategies for the South Korean navy's spare parts demand which has non-normal characteristics. ANN minimized classification errors and inventory costs, whereas LR minimized the Brier scores and the sum of forecasting errors.

• KIEAE Journal
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• v.8 no.6
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• pp.11-20
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• 2008

Modern society is an era that demands higher standards of living, and accordingly healthier living conditions due to fast economic growth. This society is being confronted by the necessity to find strategies to promote and manage health condition in everyday living environment. The current 'wellbeing' trend which pursues holistic health including physical, psychological and social health has accelerated the demand for healthy environment. In this context, this study intended to identify health friendly planning features based on consumer's demand. Web survey technique was used as main research methodology. Stratified random sampling was used with age being used as the strata valuable. Two hundred and eleven data were analyzed using SPSS statistical package. As results, awareness about health housing and hierarchy of important planning features were empirically identified. Furthermore, significant differences in some planning features according to the age were scrutinized. Major health friendly features demanded by consumers were found ventilation, non-toxic material, view of nature, space in which family can gather, protection of their privacy. Consumers' recognitions and demands varied according to age. The older the resident was, the higher the demands appeared. The results are expected to be used as a reference to explore and develop strategies for future healthy housing.

• Journal of the Korean housing association
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• v.25 no.3
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• pp.63-72
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• 2014

This study examined the special features and domestic status of the shared-house from the increasing number of single-person households, and also studied demand characteristics of the shared-house targeting young single-person household. Moreover, it found affecting factors of residential inclination on the shared-house with the binary logic model. Some of field research and interviews for the survey were conducted, and the analyzed result from this study as follows: Firstly, the domestic shared-house, introduced between the end of 2012 and early 2013, has been rapidly increased and has some features such as decreasing in housing expenses and increasing in social interaction. Secondly, the demand for shared-house by residential experience of single-person household differs according to the demographic characteristics. Thirdly, the factors that affect residential inclination of shared-house are character types, community life experience, awareness, and need for shared house.

• Steel and Composite Structures
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• v.37 no.2
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• pp.151-173
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• 2020

This paper aims to probabilistically evaluate performance of two types of I beam to box column (IBBC) connection. With the objective of considering the variability of seismic loading demand, statistical features of the inter-story drift ratio corresponding to the second, fifth and eleventh story of a 12-story steel special moment resisting frames are extracted through incremental dynamic analysis at global collapse state. Variability of geometrical variables and material strength are also taken into account. All of these random variables are exported as inputs to a probabilistic finite element model which simulates the connection. At the end, cumulative distribution functions of local seismic demand for each component of each connection are provided using histogram sampling. Through a parametric study on probabilistic local seismic demand, the influence of some geometrical random variables on the performance of IBBC connections is demonstrated. Furthermore, the probabilistic study revealed that IBBC connection with widened flange has a better performance than the un-widened flange. Also, a design procedure is proposed for WF connections to achieve a same connection performance in different stories.

• Journal of radiological science and technology
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• v.41 no.5
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• pp.451-456
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• 2018

During last a decade, there has been increased demand for 3D-printed medical devices with significant improvement of 3D-Printer (also known as Additive. Manufacturing AM), which depend upon human body features. Especially, demand for personalized medical material is highly growing with being super-aged society. In this study, 3D-reconstructed 3D mesh image from CT/MRI-images is demonstrated to analyse each patients' personalized anatomical features by using in house, then to be able to manufacture its counterpart. Developed software is distributed free of charge, letting various researcher identify biological feature for each areas.

• KIEAE Journal
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• v.9 no.2
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• pp.27-36
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• 2009

Due to rapid advances in science and technology and peoples life value, multi-dimensional functionality of the house has been possible and demanded. Among them, intellectual function and health support function appeared prominent and the former can support the later. The purpose of this study was to delineate health support planning features for smart home. Thirty six planning elements were extracted for initial pool for survey to find out what consumers demanded. Two hundred and nine data were collected through the web-survey. Important planning features were identified in relation to three different health dimensions that is physical/physiological, psychological, and social health. Generally consumers' responses were positive for all features. Major health friendly features highly demanded by consumers were found gas detect system, security system, and a call alarm system. The result of this study is expected to be used as a basic reference to develop strategies for smart home and to grasp current housing culture.

• Earthquakes and Structures
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• v.19 no.5
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• pp.379-393
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• 2020

The purpose of this study is to first evaluate the seismic behavior of ageing arch bridges by using the Intensity Measure - based demand and DCFD format, which is referred to as the fragility-hazard format. Then, an investigation is performed for their seismic vulnerability. Analytical models are created for bridges concerning different features and these models are subjected to Incremental Dynamic Analysis (IDA) analysis using a set of 22 earthquake records. The hazard curve and results of IDA analysis are employed to evaluate the return period of exceeding the limit states in the IM-based probabilistic performance-based context. Subsequently, the fragility-hazard format is used to assess factored demand, factored capacity, and the ratio of the factored demand to the factored capacity of the models with respect to different performance objectives. Finally, the vulnerability curves are obtained for the investigated bridges in terms of the loss ratio. The results revealed that decreasing the span length of the unreinforced arch bridges leads to the increase in the return period of exceeding various limit states and factored capacity and decrease in the displacement demand, the probability of failure, the factored demand, as well as the factored demand to factored capacity ratios, loss ratio, and seismic vulnerability. Finally, it is derived that the probability of the need for rehabilitation increases by an increase in the span length of the models.