• Steel and Composite Structures
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• 제34권5호
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• pp.743-767
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• 2020

Due to the impressive flexural performance, enhanced compressive strength and more constrained crack propagation, Fibre-reinforced concrete (FRC) have been widely employed in the construction application. Majority of experimental studies have focused on the seismic behavior of FRC columns. Based on the valid experimental data obtained from the previous studies, the current study has evaluated the seismic response and compressive strength of FRC rectangular columns while following hybrid metaheuristic techniques. Due to the non-linearity of seismic data, Adaptive neuro-fuzzy inference system (ANFIS) has been incorporated with metaheuristic algorithms. 317 different datasets from FRC column tests has been applied as one database in order to determine the most influential factor on the ultimate strengths of FRC rectangular columns subjected to the simulated seismic loading. ANFIS has been used with the incorporation of Particle Swarm Optimization (PSO) and Genetic algorithm (GA). For the analysis of the attained results, Extreme learning machine (ELM) as an authentic prediction method has been concurrently used. The variable selection procedure is to choose the most dominant parameters affecting the ultimate strengths of FRC rectangular columns subjected to simulated seismic loading. Accordingly, the results have shown that ANFIS-PSO has successfully predicted the seismic lateral load with R² = 0.857 and 0.902 for the test and train phase, respectively, nominated as the lateral load prediction estimator. On the other hand, in case of compressive strength prediction, ELM is to predict the compressive strength with R² = 0.657 and 0.862 for test and train phase, respectively. The results have shown that the seismic lateral force trend is more predictable than the compressive strength of FRC rectangular columns, in which the best results belong to the lateral force prediction. Compressive strength prediction has illustrated a significant deviation above 40 Mpa which could be related to the considerable non-linearity and possible empirical shortcomings. Finally, employing ANFIS-GA and ANFIS-PSO techniques to evaluate the seismic response of FRC are a promising reliable approach to be replaced for high cost and time-consuming experimental tests.

• 대한전자공학회논문지TC
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• 제46권5호
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• pp.26-35
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• 2009

OFDM (Orthogonal Frequency Division Multiplexing) 시스템은 주파수 선택적 페이딩 (frequency selective fading)과 협대역 간섭 (narrowband interference)에 강한 전송 방식으로 대용량 데이터 통신에 적합하다. 하지만 독립적으로 변조된 다수의 부반송파들이 동위상으로 중첩되면서 신호의 진폭이 증가하여 PAPR (Peak-to-Average Power Ratio)이 증가하는 문제가 발생한다. PAPR 문제를 해결하기 위해 제안된 위상회전 기법은 OFDM 신호에 위상 가중치를 곱하여 신호의 비선형 왜곡 없이 PAPR을 감소시킬 수 있지만, 위상 가중치를 탐색하는 과정에서 계산의 복잡도가 부블록 수에 따라 지수적으로 증가하는 단점이 있다. 따라서 위상회전 기법의 위상 탐색 과정에 계산의 복잡도를 감소시키면서 효율적으로 위상 가중치를 구할 수 있는 기술의 연구가 필요하다. 본 논문에서는 최적해를 구하기 위하여 사용되는 Metaheuristic 알고리즘을 위상탐색 과정에 적용하기 위한 모델링 과정을 제시하고 PTS 기법에 최적화함으로써 PAPR을 감소시키는 구조를 제안한다. 이 구조는 PTS 기법의 위상 탐색 과정에서 계산 복잡도가 지수적으로 증가하는 문제를 해결하고 PAPR 감소 성능도 보장할 수 있다. 제안하는 알고리즘을 통신 시스템에 적용하였을 때 PAPR 감소 효율을 시뮬레이션을 통해 분석했다.

• 한국수자원학회:학술대회논문집
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• 한국수자원학회 2015년도 학술발표회
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• pp.217-217
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• 2015

The objective of this study was mainly to evaluate the water resources potential of Lake Tana Basin (LTB) by using Soil and Water Assessment Tool (SWAT). From SWAT simulation of LTB, about 5236 km2 area of LTB is gauged watershed and the remaining 9878 km2 area is ungauged watershed. For calibration of model parameters, four gauged stations were considered namely: Gilgel Abay, Gummera, Rib, and Megech. The SWAT-CUP built-in techniques, particle swarm optimization (PSO) and generalized likelihood uncertainty estimation (GLUE) method was used for calibration of model parameters and PSO method were selected for the study based on its performance results in four gauging stations. However the level of sensitivity of flow parameters differ from catchment to catchment, the curve number (CN2) has been found the most sensitive parameters in all gauged catchments. To facilitate the transfer of data from gauged catchments to ungauged catchments, clustering of hydrologic response units (HRUs) were done based on physical similarity measured between gauged and ungauged catchment attributes. From SWAT land use/ soil use/slope reclassification of LTB, a total of 142 HRUs were identified and these HRUs are clustered in to 39 similar hydrologic groups. In order to transfer the optimized model parameters from gauged to ungauged catchments based on these clustered hydrologic groups, this study evaluates three parameter transfer schemes: parameters transfer based on homogeneous regions (PT-I), parameter transfer based on global averaging (PT-II), and parameter transfer by considering Gilgel Abay catchment as a representative catchment (PT-III) since its model performance values are better than the other three gauged catchments. The performance of these parameter transfer approach was evaluated based on values of Nash-Sutcliffe efficiency (NSE) and coefficient of determination (R2). The computed NSE values was found to be 0.71, 0.58, and 0.31 for PT-I, PT-II and PT-III respectively and the computed R2 values was found to be 0.93, 0.82, and 0.95 for PT-I, PT-II, and PT-III respectively. Based on the performance evaluation criteria, PT-I were selected for modelling ungauged catchments by transferring optimized model parameters from gauged catchment. From the model result, yearly average stream flow for all homogeneous regions was found 29.54 m3/s, 112.92 m3/s, and 130.10 m3/s for time period (1989 - 2005) for region-I, region-II, and region-III respectively.

• International Journal of Computer Science & Network Security
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• 제23권4호
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• pp.55-68
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• 2023

In recent years, the Television White Space (TVWS) has attracted the interest of many researchers due to its propagation characteristics obtainable between 470MHz and 790MHz spectrum bands. The plenty of unused channels in the TV spectrum allows the secondary users (SUs) to use the channels for broadband services especially in rural areas. However, when the number of SUs increases in the TVWS wireless network the aggregate interference also increases. Aggregate interferences are the combined harmful interferences that can include both co-channel and adjacent interferences. The aggregate interference on the side of Primary Users (PUs) has been extensively scrutinized. Therefore, resource allocation (power and spectrum) is crucial when designing the TVWS network to avoid interferences from Secondary Users (SUs) to PUs and among SUs themselves. This paper proposes a model to improve the resource allocation for reducing the aggregate interface among SUs for broadband services in rural areas. The proposed model uses joint power and spectrum hybrid Firefly algorithm (FA), Genetic algorithm (GA), and Particle Swarm Optimization algorithm (PSO) which is considered the Co-channel interference (CCI) and Adjacent Channel Interference (ACI). The algorithm is integrated with the admission control algorithm so that; there is a possibility to remove some of the SUs in the TVWS network whenever the SINR threshold for SUs and PU are not met. We considered the infeasible system whereby all SUs and PU may not be supported simultaneously. Therefore, we proposed a joint spectrum and power allocation with an admission control algorithm whose better complexity and performance than the ones which have been proposed in the existing algorithms in the literature. The performance of the proposed algorithm is compared using the metrics such as sum throughput, PU SINR, algorithm running time and SU SINR less than threshold and the results show that the PSOFAGA with ELGR admission control algorithm has best performance compared to GA, PSO, FA, and FAGAPSO algorithms.

• 지능정보연구
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• 제23권1호
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• pp.47-67
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• 2017

강판 표면 결함은 강판의 품질과 가격을 결정하는 중요한 요인 중 하나로, 많은 철강 업체는 그동안 검사자의 육안으로 강판 표면 결함을 확인해왔다. 그러나 시각에 의존한 검사는 통상 30% 이상의 판단 오류가 발생함에 따라 검사 신뢰도가 낮은 문제점을 갖고 있다. 따라서 본 연구는 Simultaneous MTS (S-MTS) 알고리즘을 적용하여 보다 지능적이고 높은 정확도를 갖는 새로운 강판 표면 결함 진단 시스템을 제안하였다. S-MTS 알고리즘은 단일 클래스 분류에는 효과적이지만 다중 클래스 분류에서 정확도가 떨어지는 기존 마할라노비스 다구찌시스템 알고리즘(Mahalanobis Taguchi System; MTS)의 문제점을 해결한 새로운 알고리즘이다. 강판 표면 결함 진단은 대표적인 다중 클래스 분류 문제에 해당하므로, 강판 표면 결함 진단 시스템 구축을 위해 본 연구에서는 S-MTS 알고리즘을 채택하였다. 강판 표면 결함 진단 시스템 개발은 S-MTS 알고리즘에 따라 다음과 같이 진행하였다. 첫째, 각 강판 표면 결함 별로 개별적인 참조 그룹 마할라노비스 공간(Mahalanobis Space; MS)을 구축하였다. 둘째, 구축된 참조 그룹 MS를 기반으로 비교 그룹 마할라노비스 거리(Mahalanobis Distance; MD)를 계산한 후 최소 MD를 갖는 강판 표면 결함을 비교 그룹의 강판 표면 결함으로 판단하였다. 셋째, 강판 표면 결함을 분류하는 데 있어 결함 간의 차이점을 명확하게 해주는 예측 능력이 높은 변수를 파악하였다. 넷째, 예측 능력이 높은 변수만을 이용해 강판 표면 결함 분류를 재수행함으로써 최종적인 강판 표면 결함 진단 시스템을 구축한다. 이와 같은 과정을 통해 구축한 S-MTS 기반 강판 표면 결함 진단 시스템의 정확도는 90.79%로, 이는 기존 검사 방법에 비해 매우 높은 정확도를 갖는 유용한 방법임을 보여준다. 추후 연구에서는 본 연구를 통해 개발된 시스템을 현장 적용하여, 실제 효과성을 검증할 필요가 있다.