• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 1995년도 추계학술대회 95 KFIS Workshop Realization of Human Friendly System Based on Soft Computiong Techniques
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• pp.1-54
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• 1995

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2004년도 추계학술대회 학술발표 논문집 제14권 제2호
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• pp.105-129
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• 2004

• 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.

• 인터넷정보학회논문지
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• 제23권1호
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• pp.69-76
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• 2022

Education systems have made efforts to prepare students by providing technical and nontechnical courses. With video games, however, there is the potential to develop dedicated metaverses that can help teach soft skills even during casual pastimes. The research conducted will propose a set of design practices for metaverse and game development to promote soft skills. While there are many soft skills people can acquire, this paper will focus on certain aspects based on specific games and studies. There will be some information collected from the information to support the design model and arguments. This paper will provide developers with a starting point for imaginative game creation and impart users with soft skills to assist in their professions and social life.

• Nonlinear Functional Analysis and Applications
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• 제28권3호
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• pp.753-774
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• 2023

The fundamental aim of the proposed work is to introduce the concept of soft rectangular b-metric spaces, which involves generalizing the notions of rectangular metric spaces and b-metric spaces. Furthermore, an investigation into specific characteristics and topological aspects of the underlying generalization of metric spaces is conducted. Moreover, the research establishes fixed point theorems for mappings that satisfy essential criteria within soft rectangular b-metric spaces. These theorems offer a broader perspective on established results in fixed point theory. Additionally, several congruous examples are presented to enhance the understanding of the introduced spatial framework.

• 한국정보통신학회논문지
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• 제26권2호
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• pp.325-328
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• 2022

A convolutional neural network(CNN) is widely used in the computer vision tasks, but its computing power requirement needs a design of a special circuit. Most of the computations in a CNN can be implemented efficiently in a digital circuit, but the SoftMax layer has operations unsuitable for circuit implementation, which are exponential and logarithmic functions. This paper proposes a new method to integrate the exponential and logarithmic tables of the conventional circuits into a single table. The proposed structure accesses a look-up table (LUT) only with a few maximum values, and the LUT has the result value directly. Our proposed method significantly reduces the space complexity of the SoftMax layer circuit implementation. But our resulting circuit is comparable to the original baseline with small degradation in precision.

• 대한전자공학회:학술대회논문집
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• 대한전자공학회 2001년도 하계종합학술대회 논문집(3)
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• pp.161-164
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• 2001

This paper partially presents a Hierachical neural network architecture for providing the intelligent control of complex Automatic Transmission(A/T) system which is usually nonlinear and hard to model mathematically. It consists of the module to apply or release an engine brake at the slope and that to judge the intention of the driver. The HNN architecture simplifies the structure of the overall system and is efficient for the learning time. This paper describes how the sub-neural networks of each module have been constructed and will compare the result of the intelligent A/T control to that of the conventional shift pattern.

• 한국지능시스템학회:학술대회논문집
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• 한국퍼지및지능시스템학회 2001년도 추계학술대회 학술발표 논문집
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• pp.133-136
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• 2001

This paper partially presents a Hierachical neural network architecture for providing the intelligent control of complex Automatic Transmission(AJT) system which is usually nonlinear and hard to model mathematically. It consists of the module to apply or release an engine brake at the slope and that to judge the intention of the driver. The HNN architecture simplifies the structure of the overall system and is efficient for the learning time. This paper describes how the sub-neural networks of each module have been constructed and will compare the result of the intelligent hJT control to that of the conventional shift pattern.

• Computers and Concrete
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• 제13권3호
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• pp.389-409
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• 2014

Precast hollow core slabs (HCS) are technically advanced products in the precast concrete industry, widely used in the last years due to their versatility, their multipurpose potential and their low cost. Using three dimensional FEM (Finite Element Method) elements, this study focuses on the stresses induced by the prestressing of steel. In particular the investigation of the spalling crack formation that takes place during prestressing is carried out, since it is important to assure the appropriate necessary margins concerning such stresses. In fact, spalling cracks may spread rapidly towards the web, leading to the detachment of the lower part of the slab. A parametric study takes place, capable of evaluating the influence of the tendon position and of the web width on the spalling stress. Consequently, after an extensive literature review on the topic of soft computing, an optimization of the HCS is performed by means of Genetic Algorithms coupled with 3-D FEM models.

• 전자공학회논문지CI
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• 제41권6호
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• pp.55-60
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• 2004

결정된 변속선도에 의한 자동변속 패턴은 운전자에게 편리한 변속을 제공한다. 하지만, 운전자의 운전 성향이 개인마다 다양함으로 고정된 변속선도를 여러 운전자에게 동일하게 제공하는 것은 불만의 요소로 인식되고 있다. 이에, 본 논문에서는 운전자의 성향을 결정할 수 있는 입력을 이용한 학습 모듈을 설계하여 운전 성향을 판단하고자 한다. 판단된 운전 성향을 이용하여 변속선도를 조정함으로써 운전자의 의지에 부합되는 변속패턴을 제공하고자 한다. 실제 주행 시 얻은 데이터를 이용하여 제안된 모듈의 성능의 우수함을 보인다.