• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.3
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• pp.18-31
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• 2002

In this study, we introduce a concept of advanced neurofuzzy polynomial networks(ANFPN), a hybrid modeling architecture combining neurofuzzy networks(NFN) and polynomial neural networks(PNN). These networks are highly nonlinear rule-based models. The development of the ANFPN dwells on the technologies of Computational Intelligence(Cl), namely fuzzy sets, neural networks and genetic algorithms. NFN contributes to the formation of the premise part of the rule-based structure of the ANFPN. The consequence part of the ANFPN is designed using PNN. At the premise part of the ANFPN, NFN uses both the simplified fuzzy inference and error back-propagation learning rule. The parameters of the membership functions, learning rates and momentum coefficients are adjusted with the use of genetic optimization. As the consequence structure of ANFPN, PNN is a flexible network architecture whose structure(topology) is developed through learning. In particular, the number of layers and nodes of the PNN are not fixed in advance but is generated in a dynamic way. In this study, we introduce two kinds of ANFPN architectures, namely the basic and the modified one. Here the basic and the modified architecture depend on the number of input variables and the order of polynomial in each layer of PNN structure. Owing to the specific features of two combined architectures, it is possible to consider the nonlinear characteristics of process system and to obtain the better output performance with superb predictive ability. The availability and feasibility of the ANFPN are discussed and illustrated with the aid of two representative numerical examples. The results show that the proposed ANFPN can produce the model with higher accuracy and predictive ability than any other method presented previously.

• Spatial Information Research
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• v.11 no.2
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• pp.101-117
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• 2003

High resolution satellite image analysis has been recognized as an effective technique for monitoring local land-cover and atmospheric changes. In this study, a new high resolution map for land-cover was generated using both high-resolution IKONOS image and conventional land-use mapping. Fuzzy classification method was applied to classify land-cover, with minimum operator used as a tool for joint membership functions. In separateness analysis, the values were not great for all bands due to discrepancies in spectral reflectance by seasonal variation. The land-cover map generated in this study revealed that conifer forests and farm land in the ground and tidal flat and beach in the ocean were highly changeable. The kappa coefficient was 0.94% and the overall accuracy of classification was 95.0%, thus suggesting a overall high classification accuracy. Accuracy of classification in each class was generally over 90%, whereas low classification accuracy was obtained for classes of mixed forest, river and reservoir. This may be a result of the changes in classification, e.g. reclassification of paddy field as water area after water storage or mixed use of several classification class due to similar spectral patterns. Seasonal factors should be considered to achieve higher accuracy in classification class. In conclusion, firstly, IKONOS image are used to generated a new improved high resolution land-cover map. Secondly, IKONOS image could serve as useful complementary data for decision making when combined with GIS spatial data to produce land-use map.

• Journal of Korea Water Resources Association
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• v.51 no.11
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• pp.977-987
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• 2018

The purpose of the water distribution system is gradually changing to increase the flexibility for responding to various abnormal situations. In addition, it is essential to improve resilience through preparing emergency plans against water supply failure. The most efficient way is emergency interconnections which supply water from interconnected adjacent blocks. To operate successful interconnections, it is essential to evaluate the supply performance in spatial and temporal aspects. The spatial and temporal aspects are dominated by its interconnected pipes and interconnected reservoirs respectively. In this study, an emergency interconnection scenario where problem occurred in reservoir 1 at 0:00hr in A city, Korea. An Advanced-Pressure Driven Analysis model was used to simulate the volume and inflow volume of the interconnected reservoirs. Based on the hydraulic analysis results, a multi-dimensional evaluation of the supply performance was conducted by applying possible water supply range indicator (PWSRI) and possible water supply temporal indicator (PWSTI) which are based on fuzzy membership functions. As a result, it was possible to evaluate the supply performance on the sides of consumers in spatio-temporal aspects and to review whether established plans mitigate the damage as intended. It is expected to be used for decision making on structural and non-structural emergency plan to improve the performance of an emergency interconnection.

• Proceedings of the Plant Resources Society of Korea Conference
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• 2023.04a
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• pp.38-38
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• 2023

Sorghum (Sorghum bicolor L.) is a promising biomass crop with a high lignocellulose content. This study aimed to select high salt-tolerance sorghum lines for cultivation on reclaimed land. Using 7-day seedlings of the sorghum population consisted of 71 radiation-derived mutants (M₂ to M₆) and 33 genetic resources, survival rate (SR), plant height (PH), root length (RL), fresh weight (FW), and chlorophyll content (CC) were measured for two weeks after 102 mM (0.6%) NaCl treatment. Furthermore, the characteristics of the sorghum population were confirmed using correlation analysis, PCA (principal component analysis), and the FCE (fuzzy comprehensive evaluation) method. Under 102 mM NaCl conditions, SR ranged from 4.9 (IS645-200-6) to 82.4% (KLSo79125-200-1), with an average of 49.9%. PH varied from 7.5 (Mesusu-100-2) to 33.2 cm (DINE-A-MITE-100-2-10), with an average of 20.4 cm. RL ranged from 1.0 (IS645-200-1) to 17.0 cm (30-100-2), with an average of 7.7 cm. FW varied from 0.1 (IS645-200-6) to 4.5 g/plant (DINE-A-MITE-100-2-10), with an average of 2.1 g/plant. CC ranged from 0.9 (DINE-A-MITE-100-2-2) to 3.1 mg/g (IS12937), with an average of 1.7 mg/g. An overall positive correlation, with SR and FW (r = 0.86, P < 0.01), and FW and CC (r = 0.79, P < 0.01), was shown by correlation analysis. Among the five traits, two principal components were extracted by PCA analysis. PC1 was significantly associated with FW, while PC2 was highly involved with RL. To evaluate the salt tolerance level of the sorghum population when an FCE based on trait data was performed, MFV (membership function value) was 0.68. As a result of compiling the MFV of each line, eight lines with MFV > 0.68 were selected. Ultimately, the radiation-derived mutant lines, DINE-A-MITE-100-2-10 and DINE-A-MITE-100-2-12 were selected as salt-tolerant sorghum lines. The results are expected to inform salt-tolerant sorghum breeding programs, and the high salt-tolerance sorghum lines might be advantageous for cultivation on reclaimed land.