• Proceedings of the KIEE Conference
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• 1998.07b
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• pp.566-568
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• 1998

In this paper, we suggest a optimal design method of Fuzzy-Neural Networks model for complex and nonlinear systems. FNNs have the stucture of fusion of both fuzzy inference with linguistic variables and Neural Networks. The network structure uses the simpified inference as fuzzy inference system and the BP algorithm as learning procedure. And we use a clustering algorithm to find initial parameters of membership function. The parameters such as membership functions, learning rates and momentum coefficients are easily adjusted using the genetic algorithms. Also, the performance index with weighted value is introduced to achieve a meaningful balance between approximation and generalization abilities of the model. To evaluate the performance index, we use the time series data for gas furnace and the sewage treatment process.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.3004-3006
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• 2000

In this paper, we propose an optimal design method of Fuzzy-Neural Networks model with parallel structure for complex and nonlinear systems. The proposed model is consists of a multiple number of FNN connected in parallel. The proposed FNNs with parallel structure is based on Yamakawa's FNN and it uses simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rules. We use a HCM clustering and GAs to identify the structure and the parameters of the proposed model. Also, a performance index with a weighting factor is presented to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model. we use the time series data for gas furnace and the numerical data of nonlinear function.

• Proceedings of the KIEE Conference
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• 1998.11b
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• pp.654-656
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• 1998

This paper presents an optimal identification method of nonlinear and complex system that is based on fuzzy-neural network(FNN). The FNN used simplified inference as fuzzy inference method and Error Back Propagation Algorithm as learning rule. And we use a HCM Algorithm to find initial parameters of membership function. And then to obtain optimal parameters, we use the genetic algorithm. Genetic algorithm is a random search algorithm which can find the global optimum without converging to local optimum. The parameters such as membership functions, learning rates and momentum coefficients are easily adjusted using the genetic algorithms. Also, the performance index with weighted value is introduced to achieve a meaningful balance between approximation and generalization abilities of the model. To evaluate the performance of the FNN, we use the time series data for 9as furnace and the sewage treatment process.

• Structural Engineering and Mechanics
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• v.54 no.3
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• pp.453-474
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• 2015

A hybrid approach of Particle Swarm Optimization (PSO) and Swallow Swarm Optimization algorithm (SSO) namely Hybrid Particle Swallow Swarm Optimization algorithm (HPSSO), is presented as a new variant of PSO algorithm for the highly nonlinear dynamic truss shape and size optimization with multiple natural frequency constraints. Experimentally validation of HPSSO on four benchmark trusses results in high performance in comparison to PSO variants and to those of different optimization techniques. The simulation results clearly show a good balance between global and local exploration abilities and consequently results in good optimum solution.

• Proceedings of the KIEE Conference
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• 2001.07d
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• pp.2669-2671
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• 2001

In this paper, we propose design a Multi-Fuzzy Inference model structure. In order to determine structure of the proposed Multi-Fuzzy Inference model, HCM clustering method is used. The parameters of membership function of the Multi-Fuzzy are identified by genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. We use simplified inference and linear inference as inference method of the proposed Multi-Fuzzy model and the standard least square method for estimating consequence parameters of the Multi-Fuzzy. Finally, we use some of numerical data to evaluate the proposed Multi-Fuzzy model and discuss about the usefulness.

• Proceedings of the KIEE Conference
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• 1999.07g
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• pp.2911-2913
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• 1999

This paper suggest an optimal identification method to complex and nonlinear system modeling that is based on Fuzzy-Neural Network(FNN). The FNN modeling implements parameter identification using HCM algorithm and optimal identification algorithm structure combined with two types of optimization theories for nonlinear systems, we use a HCM Clustering Algorithm to find initial parameters of membership function. The parameters such as parameters of membership functions, learning rates and momentum coefficients are adjusted using optimal identification algorithm. The proposed optimal identification algorithm is carried out using both a genetic algorithm and the improved complex method. Also, an aggregate objective function(performance index) with weighted value is proposed to achieve a sound balance between approximation and generalization abilities of the model. To evaluate the performance of the proposed model, we use the time series data for gas furnace, the data of sewage treatment process and traffic route choice process.

• The Journal of Korean Academy of Sensory Integration
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• v.17 no.1
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• pp.9-18
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• 2019

Objective : This study investigated the effect of intensive weight shift training (IWST) on the ability to balance in a sitting posture of children with spastic cerebral palsy (SCP). Methods : One child with spastic diplegia participated in this study for a total of 8 weeks using the ABA experimental design. For the pre-intervention period (A1), general physical therapy (GPT) for children with SCP was performed. The intervention period (B1 and B2), GPT and IWST were conducted for children with SCP, and GPT was conducted again for the post-intervention period (A'1 and A'2). Trunk control capacity was measured using the Korean Trunk Control Measurement Scale (TCMS-K) and Biorescue (RM Ingenierie, France). Results : All TCMS-K variables increased from A1 to B2, and decreased from B2 to A'2. The total area with limit of stability (LOS) increased from A1 to B2, and decreased from B2 to A'2. The ratio of the left/right (Lt/Rt) and anterior/posterior (Ant/Post) LOS area was closer to 1, meaning symmetry, in B2 than in A1. The ratio of the Lt/Rt LOS area decreased further from 1 in A'2 than in B2. The ratio of the Ant/Post LOS area was closer to 1 in A'2 than in B2. Conclusion : IWST had a positive effect on the improvement of balance in the sitting posture of a child with SCP. The results suggest that IWST might help to improve the balance abilities of children with SCP for independent sitting, postural control, and activities of daily living.

• Journal of the Korean Institute of Intelligent Systems
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• v.10 no.5
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• pp.487-496
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• 2000

In this paper, the Multi-FNN(Fuzzy-Neural Networks) model is identified and optimized using HCM(Hard C-Means) clustering method and genetic algorithms. The proposed Multi-FNN is based on Yamakawa's FNN and uses simplified inference as fuzzy inference method and error back propagation algorithm as learning rules. We use a HCM clustering and Genetic Algorithms(GAs) to identify both the structure and the parameters of a Multi-FNN model. Here, HCM clustering method, which is carried out for the process data preprocessing of system modeling, is utilized to determine the structure of Multi-FNN according to the divisions of input-output space using I/O process data. Also, the parameters of Multi-FNN model such as apexes of membership function, learning rates and momentum coefficients are adjusted using genetic algorithms. A aggregate performance index with a weighting factor is used to achieve a sound balance between approximation and generalization abilities of the model. The aggregate performance index stands for an aggregate objective function with a weighting factor to consider a mutual balance and dependency between approximation and predictive abilities. According to the selection and adjustment of a weighting factor of this aggregate abjective function which depends on the number of data and a certain degree of nonlinearity, we show that it is available and effective to design an optimal Multi-FNN model. To evaluate the performance of the proposed model, we use the time series data for gas furnace and the numerical data of nonlinear function.

• Herbal Formula Science
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• v.10 no.2
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• pp.1-4
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• 2002

The development of Korean Oriental medicine is based upon the accumulation of experience and knowledge gathered over the centuries. The approaches taken are holistic and empirical. There is a need to understand their actions at molecular levels with more rational, objective and scientific studies. Today it appears that Chronic and age-associated diceases may be multifactorial and hence more complex. A different approach may be required. One claimed usage of Korean Oriental medicine is for the treatment and prevention of chronic and age-associated illnesses. Some of the botanical formulas used for this purpose were discovered thousands of years ago and continue to be used today. There are indications that these formulas may indeed be helpful in the treatment or prevention of chronic diseases. This multi-component medicine could not only be very useful meeting the unmet clinical needs but for defining a more synergistic therapy that supports and maintains the bodies natural curative abilities. The potential usefulness of Korean Oriental medicine embodies the belief of maintaining healthy homeostasis of the body through the proper balance of a mixture of chemical at different organs or tissues. This concept is different from western medicine and implies that multiple compounds may act on multiple mechanisms of action to maintain the balance of the complex web of biology. This is very important in view of sciences current direction to integrate fragmented information to develop future medicines. The western and eastern approaches to human health and disease are complementary to each other. The best approach in developing future medicines is to integrate both approaches.

• Journal of the Ergonomics Society of Korea
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• v.35 no.6
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• pp.493-501
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• 2016

Objective: This study analyzes the effect of angle conditions of rehabilitation equipment used for supporting hemiplegic patients on their rehabilitation training for standing action. The study was performed by adjusting the rear angle of seat inclination through a motion analysis. Background: Owing to a loss of muscle rigidity and degradation of muscle control ability, hemiplegic stroke patients suffer from asymmetrical posture, abnormal body balance, and degraded balance abilities due to poor weight-shifting capacity. The ability to shift and maintain one's weight is extremely essential for mobility, which plays an important role in our daily life. Thus, to improve patients' ability to maintain weight evenly and move normally, they need to undergo orthostatic and ambulatory training. Method: Using a motion analysis system, knee movements on both hemiplegic side and non-hemiplegic side were measured and analyzed in five angles ($0^{\circ}$, $10^{\circ}$, $30^{\circ}$, $50^{\circ}$, $70^{\circ}$) while supported by the sit-to-stand rehabilitation equipment. Results: The knee movements on both sides increased as the angle increased in angle support interval to support a hemiplegic patient's standing up position. In standing up interval, a hemiplegic patient's knee movement deviations on both sides decreased, and the movement differences between hemiplegic and non-hemiplegic legs also decreased as the angle increased. Conclusion: The results of this study showed that the rehabilitation effectiveness increases as the angle increases, leading to a balanced standing posture through the decrease of movement difference between hemiplegic and non-hemiplegic sides and an improved standing up ability through the increase of knee movement on both sides. However, angles higher than $50^{\circ}$ didn't provide a significant effect. Therefore, a support angle under $50^{\circ}$ was proposed in this study. Application: The results of this study are expected to be applicable to the design of sit-to-stand support equipment to improve the effectiveness of the rehabilitation process of hemiplegic patients.