• International Journal of Computer Science & Network Security
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• 제22권2호
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• pp.131-138
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• 2022

Soft sensors are used to anticipate complicated model parameters using data from classifiers that are comparatively easy to gather. The goal of this study is to use artificial intelligence techniques to design and build soft sensors. The combination of a Long Short-Term Memory (LSTM) network and Grey Wolf Optimization (GWO) is used to create a unique soft sensor. LSTM is developed to tackle linear model with strong nonlinearity and unpredictability of manufacturing applications in the learning approach. GWO is used to accomplish input optimization technique for LSTM in order to reduce the model's inappropriate complication. The newly designed soft sensor originally brought LSTM's superior dynamic modeling with GWO's exact variable selection. The performance of our proposal is demonstrated using simulations on real-world datasets.

• 국제학술발표논문집
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• The 1th International Conference on Construction Engineering and Project Management
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• pp.744-747
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• 2005

The AEC (Architecture/Engineering/Construction) industry is facing a competitive world after it entered into the 21^st century. Due to improper planning and scheduling, the construction projects face severe delays in completion. Most of the present day construction organisations operate in multiple project environments where more than one projects are to be managed simultaneously. But the advantages of planning and scheduling as multiple projects have not been utilized by these organisations. Change in multi-project planning and scheduling is inevitable and often frequent, therefore the traditional planning and scheduling approaches are no more feasible in scheduling multiple construction projects. The traditional scheduling tools like CPM and PERT do not offer any help in scheduling in a resource-constrained environment. This necessitated a detailed study to model the environment realistically and to make the allocation of limited resources flexible and efficient. This paper delineates about the proactive model which will help the project managers for scheduling the multiple construction projects.

• 한국심리학회지 : 문화 및 사회문제
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• 제14권1호_spc
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• pp.349-365
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• 2008

한국 문화와 한국인의 정서를 반영하는 한국적 상담모형의 대안으로 현실역동상담이 제안된 바 있다. 본 연구에서는 국가청소년위원회 산하인 청소년상담지원센터에서 의뢰한 아들에게 폭행을 당한 부모를 상담하면서 현실역동상담의 특성이 어떻게 드러나고 있는지를 질적으로 분석했다. 현실역동상담의 일곱 가지 주요 특성은 한국사회가 체면사회인 만큼 전체적 맥락을 고려해 문제 파악하기, 내적세계 뿐만 아니라 외적인 현실세계 중시하기, 관계 속에서의 역할 강조하기, 상담자가 양육자 내지는 교육자와 같은 역할하기, 내담자가 깨어나도록 직면시키기, 부모-자녀간의 관계회복 도모하기, 사람들과의 관계 속으로 내담자를 밀어 넣기인데, 이러한 것들이 부모를 폭행하는 아들을 둔 부모에 대한 상담과정에서 명료하게 드러났다. 본 연구에서는 상담자와 내담자 간에 이루어진 대화의 원자료가 너무 길고, 또 그것만으로는 무엇이 어떻게 진행되었는지가 선명하게 드러나지 않기 때문에 상담자 자신의 해설이 곁들여진 사례보고를 분석하는 방식을 채택했다.

• 대한안전경영과학회지
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• 제10권2호
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• pp.187-193
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• 2008

Cross docking is a warehouse management concept in which items delivered to a distribution facility by inbound trucks are immediately sorted out and reorganized based on customer demands and are routed and loaded into outbound trucks for delivery to customers without actually being held in inventory in the distribution facility. In this research, the design of distribution facility for cross docking systems was studied. The objective of this research is to find the minimum number of receiving docks and shipping docks, respectively, in order to meet the daily demand of the distribution center. Two solution approaches are employed in modeling and solving the problem The first approach is mathematical modeling and the second approach is a simulation. The logic developed in the simulation model is expected to apply to the real world situation.

• 경영과학
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• 제17권2호
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• pp.87-95
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• 2000

This paper presents two analytical approaches to determine the vehicle fleet size for container shuttle service. The shuttle service can be defined as the repetitive travel between the designated places during working period. In the first approach, the transportation model is adopted in order to determine the number of vehicles required. Its advantages and disadvantages in practical application are also discussed. In the second approach, a logical network which is oriented on job is transformed from a physical network which is focused on demand site. Nodes on the logical network represent jobs which include loaded travel, loading and unloading and arcs represent empty travel for the next jobs which include loaded travel, loading and unloading and arcs represent empty travel for the next job. Then a mathematical formulation is constructed similar to the multiple traveling salesman problem (TSP). A solution procedure is carried out based on the well-known insertion heuristic with the real world data.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1993년도 한국자동제어학술회의논문집(국내학술편); Seoul National University, Seoul; 20-22 Oct. 1993
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• pp.106-112
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• 1993

A new model for the construction of a sonar map in a specular environment has been developed ad implemented. In a real world where most of the object surfaces are specular ones, a sonar sensor suffers from a multipath effect which results in a wrong interpretation of an objects's location. To reduce this effect and hence to construct a reliable map of a robot's surroundings, a probabilistic approach based on Bayesian reasoning is adopted to both evaluation of object orientations and estimation of an occupancy probability of a cell by an object. The usefulness of this approach is illustrated with the results produced by our mobile robot equipped with ultrasonic sensors.

• Transactions on Control, Automation and Systems Engineering
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• 제1권2호
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• pp.147-152
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• 1999

It is an interesting area in the field of artifical intelligence to find an analytic model of cooperative structure for multiagent system accomplishing a given task. Usually it is difficult to design controllers for multi-agent systems without a comprehensive knowledge about the system. One of the way to overcome this limitation is to implement an evolutionary approach to design the controllers. This paper introduces the use of a genetic algorithm to discover a fuzzy logic controller with rules that govern emergent agents solving a pursuit problem in a continuous world. Simulation results indicate that, given the complexity of the problem, an evolutionary approach to find the fuzzy logic controller seems to be promising.

• 품질경영학회지
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• 제42권1호
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• pp.91-109
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• 2014

Purpose: This study compares quality crisis and management at Hyundai Motor in the late 1990s and Toyota Motor in the late 2000s. We can expect to induce more meaningful policy implications in quality management from this in-depth comparative case study. Methods: This study compares two cases at Hyundai and Toyota Motor how to overcome quality crisis based on the OESP (Organization-Environments-Strategy- Performance) model. Results: Hyundai Motor shows centralized approach based on the asymmetric organizational culture and the entrepreneurial leadership but Toyota shows decentralized, systematic approach based on the steady state leadership and symmetric organizational culture. The CEO's leadership have proved to be one of the important factors at both companies. Conclusion: The effective quality management in global contexts has become more and more difficult for the 'complexity explosions' in automobile industry. As a consequence, the future competitive edge of world automobile industry will come from the effective quality management of products in global contexts.

• 인터넷정보학회논문지
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• 제23권2호
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• pp.97-105
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• 2022

Web services show a rapid evolution and integration to meet the increased users' requirements. Thus, web services undergo updates and may have performance degradation due to undetected faults in the updated versions. Due to these faults, many performances and regression anomalies in web services may occur in real-world scenarios. This paper proposed applying the deep learning model and innovative explainable framework to detect performance and regression anomalies in web services. This study indicated that upper bound and lower bound values in performance metrics provide us with the simple means to detect the performance and regression anomalies in updated versions of web services. The explainable deep learning method enabled us to decide the precise use of deep learning to detect performance and anomalies in web services. The evaluation results of the proposed approach showed us the detection of unusual behavior of web service. The proposed approach is efficient and straightforward in detecting regression anomalies in web services compared with the existing approaches.

• The Journal of Asian Finance, Economics and Business
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• 제7권12호
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• pp.109-114
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• 2020

The aim of this study is to develop basic artificial neural network models in forecasting the in-sample gross domestic product (GDP) of Malaysia. GDP is one of the main indicators in presenting the macro economic condition of a country as set by the world authority bodies such as the World Bank. Hence, this study uses an artificial neural network-based approach to make predictions concerning the economic growth of Malaysia. This method has been proposed due to its ability to overcome multicollinearity among variables, as well as the ability to cope with non-linear problems in Malaysia's growth data. The selected inputs and outputs are based on the previous literatures as well as the economic growth theory. Therefore, the selected inputs are exports, imports, private consumption, government expenditure, consumer price index (CPI), inflation rate, foreign direct investment (FDI) and money supply, which includes M1 and M2. Whilst, the output is real gross domestic product growth rate. The results of this study showed that the neural network method gives the smallest value of mean error which is 0.81 percent with a total difference of 0.70 percent. This implies that the neural network model is appropriate and is a relevant method in forecasting the economic growth of Malaysia.