• Journal of Korean Society for Quality Management
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• v.51 no.4
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• pp.573-588
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• 2023

Purpose: This study presents a research approach that utilizes deep reinforcement learning to construct optimal portfolios based on the business cycle for stocks and other assets. The objective is to develop effective investment strategies that adapt to the varying returns of assets in accordance with the business cycle. Methods: In this study, a diverse set of time series data, including stocks, is collected and utilized to train a deep reinforcement learning model. The proposed approach optimizes asset allocation based on the business cycle, particularly by gathering data for different states such as prosperity, recession, depression, and recovery and constructing portfolios optimized for each phase. Results: Experimental results confirm the effectiveness of the proposed deep reinforcement learning-based approach in constructing optimal portfolios tailored to the business cycle. The utility of optimizing portfolio investment strategies for each phase of the business cycle is demonstrated. Conclusion: This paper contributes to the construction of optimal portfolios based on the business cycle using a deep reinforcement learning approach, providing investors with effective investment strategies that simultaneously seek stability and profitability. As a result, investors can adopt stable and profitable investment strategies that adapt to business cycle volatility.

• Journal of the Economic Geographical Society of Korea
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• v.20 no.2
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• pp.189-213
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• 2017

This study seeks to critically examine the significance and limits of the cluster adaptive cycle model for analysis of cluster evolution and to propose research issues for future analysis of cluster evolution based on this critical examination. Until the 1980s, research on industrial complexes including clusters was based on a 'static perspective' that focuses on the aspect of economic space at a specific point in time, but the research paradigm has recently shifted to a 'dynamic perspective' focusing on 'evolution' of 'complex adaptive systems'. As a result, the adaptive cycle model has attracted attention as an analysis tool of dynamically evolving clusters. However, the cluster adaptive cycle model has emerged by being appropriately modified and expanded according to the properties of the cluster and its evolution. The cluster adaptive cycle model is a comprehensive analysis framework that identifies the characteristics of cluster evolution in terms of resource accumulation, interdependence, and resilience and classifies cluster evolution paths into six different categories. Nevertheless, there is still a need for further discussion and supplementation in terms of theoretical and empirical research to expand and deepen the model. Therefore, research issues for future analysis of cluster evolution are to specify and elaborate the cluster evolution model, to emphasize the concept of resilience, and to verify the applicability and usefulness of the model through empirical research.

• Economic Analysis
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• v.24 no.3
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• pp.1-36
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• 2018

When it comes to explaining the relationship between inventory investment and business fluctuations, the production smoothing theory and the stock-out avoidance theory take contradictory stances. Decision-making related to inventory investments of corporations is thought to be influenced by both motives, but the relative sizes or directions of their respective influences can differ depending upon the phase of the business cycle. Against this backdrop, this paper differs from existing studies in that it theoretically tests the relative significances of the production smoothing and stock-out avoidance motives in the inventory investment dynamics, while placing its analytical focus on determining the existence and patterns of the asymmetric dynamics of inventory investment over the business cycle phases. To this end this paper sets up a non-linear model that is expanded from the existing linear inventory investment model, and checks whether its predictive power is better than that of the existing model. The results of analysis confirm the nature of the asymmetric dynamics of inventory investment over the business cycle phases. A stock-out avoidance motive appears but there is no significant production smoothing motive in boom times. In downturns, in contrast, the stock-out avoidance motive is insignificant, but a quality of asymmetric dynamics in which changes in inventory cause the deepening of recessions, due to the non-convexity of production costs proposed by Ramey (1991), is detected. This paper confirms that a model considering the asymmetric dynamics of inventory investment can have better predictive power than one that does not consider it, through within-sample and out-of-sample predictions and various predictive power tests. These research results are expected to be useful for economic forecasting, through their enhancement of the understandings of the inventory investment dynamics and of the nature of its business cycle destabilization.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 1997.10a
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• pp.115-120
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• 1997

Environmental Product Life Cycle Management is an activity for defining and describing the product, process or activity environmentally. Especially, the main responsibility for the environmental impact of products lies in the design phase of product. Designers cany a heavy responsibility to determine technical, economic and ecological properties of the product. So in order to help designers, structured understanding and application of treating large amount of data and infonnation should be considered. This paper presents a methodological approach for decision supporting to build Product Life Cycle Management system and show a set of database modeling. Additionally, a key issue for databases is the quality of the provided information.

• Korean Journal of Air-Conditioning and Refrigeration Engineering
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• v.24 no.6
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• pp.538-544
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• 2012

Analysis of thermal performance is required for the economic operation of turbine cycle of power plant. We developed corrective model of main feed water flow which is the most important parameter for the precise analysis of turbine cycle performance. Classification model for the identification of feed water flow measurement status was applied to increase the suitability of the corrective model. We used neural network and support vector machine to develop estimation model of main feed water flow with more generalization capability. The estimation model can be used practically to evaluate corrective performance of turbine cycle plant.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.40 no.1
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• pp.77-85
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• 2020

Currently, life-cycle cost analysis methods are introduced to maintain large infrastructure facilities in Korea. However, there are not many cases in which maintenance models are applied that reflect conditions such as the location of a facility and its surroundings. In order to establish an appropriate maintenance strategy, a cost prediction, deterioration model, and a decision model reflecting uncertainty should be established. In this study, an economic analysis model was developed for long-term cost planning and management based on user decisions based on maintenance methods and judgment criteria for painting specifications applied to power generation structures. The performance of the paintwork was assessed through the paint deterioration test for the application of the economic analysis model, and the results of the economic analysis according to the applied paint specifications (Urethan, polysiloxane, fluorine) were verified by applying the proposed economic analysis model. In this study, it is believed that the selection of the repair cycle and evaluation methods applied with the development model rather than the performance of the painting can be expected to be used as basic data for the maintenance cycle, even if it is not limited to the painting.

• Advances in Energy Research
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• v.4 no.2
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• pp.121-146
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• 2016

This study is concerned with the analysis of two renewable technologies for electric energy production: wind energy and photovoltaic energy. The two technologies were assessed and compared by economic point of view, by using selected indicators characterized by a clear calculation approach, requirement of information easy to be collected, clear, but even complete, interpretation of results. The used economic indicators are Levelized Cost of Energy, $CO_2$ abatement cost and fossil fuel saving specific cost; these last two specifically aimed at evaluating the different capabilities that renewable technologies have to cut down direct $CO_2$ emissions and to avoid fossil fuel extraction. The two technologies were compared also from the environmental point of view by applying Life Cycle Assessment approach and using the environmental impact categories from the Eco-indicator'95 method. The economic analysis was developed by taking into account different energy system sizes and different geographic areas in order to compare different European conditions (Italy, Germany and Denmark) in term of renewable resource availability and market trend. The environmental analysis was developed comparing two particular types of PV and wind plants, respectively residential and micro-wind turbine, located in Italy. According to the three calculated economic indicators, the wind energy emerged as more favorable than PV energy. From the environmental point of view, both the technologies are able to provide savings for almost all the considered environmental impact categories. The proposed approach, based on the use of economic and environmental indicators may be useful in supporting the policies and the decision making procedures concerned with the promotion and use of renewables, in reference to the specific geographic, economic and temporal conditions.

• Solar Energy
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• v.10 no.1
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• pp.63-79
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• 1990

It has been recognized that a policy for supplying solar house and hot water production systems utilizing solar energy needs to be driven to save civilian comsuming energy or to develop alternative energy. However, the economic feasibility study of solar energy systems must be carried out before their practical use. The purpose of this study is to furnish information for supplying policy and enlightening users with the economic feasibility study of solar house and hot water production systems. Decision support systems are established to carry out economic analysis on solar systems more accurately. Therefore, computer simulation is carried out to analyze the performance of solar systems and also economic feasibility study by trial and error method is carried out. Fuel cost and additional cost for solar systems are estimated employing present worth concept and economic analysis has been conducted using the break-even point analysis method and life-cycle cost analysis method.

• Korean Chemical Engineering Research
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• v.52 no.4
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• pp.503-515
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• 2014

A lot of existing wastewater treatment plants (WWTPs) are rebuilt or retrofitted for advanced wastewater treatment processes to cope with reinforced effluent criteria of nitrogen and phosphorous. Moreover, how to treat the wasted sludge from WWTPs has been also issued since the discharge of the wasted sludge into ocean is impossible from 2011 due to the London Convention 97 protocol. These trend changes of WWTPs get a motivation to assess environmental and economic impacts from the construction stage to the waste stage in WWTPs. Therefore, this study focuses on evaluation of environmental and economic impacts of the advanced wastewater treatment processes and waste sludge treatment process by using life cycle assessment. Four advanced wastewater treatment processes of Anaerobic/Anoxic/Oxic ($A_2O$), 5 stages-Bamard Denitrification Phosphate (Bardenpho), Virginia Initiative Plant (VIP), and Modified University of Cape Town (MUCT) are chosen to compare the conventional activated sludge (CAS) and three waste sludge treatment methods of land fill, incineration, and composting are used. To evaluate environmental and economic impacts of each advanced wastewater treatment processes, life cycle assessment (LCA) and life cycle cost (LCC) are conducted based on International organization for standardization (ISO) guidelines. The results clearly represent that the $A_2O$ process with composting shows 52% reduction in the environmental impact than the CAS process with landfill. On the other hand, the MUCT process with composting is able to save 62% of the life cycle cost comparing with the CAS process with landfill. This result suggested the qualitative and quantitative criteria for evaluating eco-environmental and economic technologies of advanced treatment processes and also sludge treatment method, where their main influence factors on environmental and economic impacts are analyzed, respectively. The proposed method could be useful for selecting the most efficient and eco-friendly wastewater treatment process and sludge treatment method when retrofitting the existing WWTPs to advanced treatments.

• Journal of the military operations research society of Korea
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• v.28 no.1
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• pp.97-114
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• 2002

An estimation of economic life for a new weapon system is a critical issue in aquisition process. In general a life cycle cost consists of, development cost, aquisition cost, and maintenance cost. These costs are not identified and obtained in the beginning of the aquisition process. This paper deals with an economic life for KlAl tank which is being deployed recently, using PRICE model. In order to estimate an KlAl economic life, we use equivalent annual cost method which is sum of capital recovering with return and equivalent O&M cost method. This method determines an economic life by minimizing annual investment cost and operation and maintenance cost. In this paper, an aquisition cost of KlAl is obtained from PRICE H and O&M cost from PRICE HL model. We obtained various results depending upon production quantity. An economic life for KlAl is estimated 18 years when 300 tanks are produced.