• 제목/요약/키워드: Adaptive neuro fuzzy interference system

검색결과 4건 처리시간 0.017초

Application of Adaptive Neuro-Fuzzy Inference System for Interference Management in Heterogeneous Network

  • Palanisamy, Padmaloshani;Sivaraj, Nirmala
    • ETRI Journal
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    • 제40권3호
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    • pp.318-329
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    • 2018
  • Femtocell (FC) technology envisaged as a cost-effective approach to attain better indoor coverage of mobile voice and data service. Deployment of FCs over macrocell forms a heterogeneous network. In urban areas, the key factor limits the successful deployment of FCs is inter-cell interference (ICI), which severely affects the performance of victim users. Autonomous FC transmission power setting is one straightforward way for coordinating ICI in the downlink. Application of intelligent control using soft computing techniques has not yet explored well for wireless networks. In this work, autonomous FC transmission power setting strategy using Adaptive Neuro Fuzzy Inference System is proposed. The main advantage of the proposed method is zero signaling overhead, reduced computational complexity and bare minimum delay in performing power setting of FC base station because only the periodic channel measurement reports fed back by the user equipment are needed. System level simulation results validate the effectiveness of the proposed method by providing much better throughput, even under high interference activation scenario and cell edge users can be prevented from going outage.

Application of ANFIS Power Control for Downlink CDMA-Based LMDS Systems

  • Lee, Ze-Shin;Tsay, Mu-King;Liao, Chien-Hsing
    • ETRI Journal
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    • 제31권2호
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    • pp.182-192
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    • 2009
  • Rain attenuation and intercell interference are two crucial factors in the performance of broadband wireless access networks such as local multipoint distribution systems (LMDS) operating at frequencies above 20 GHz. Power control can enhance the performance of downlink CDMA-based LMDS systems by reducing intercell interference under clear sky conditions; however, it may damage system performance under rainy conditions. To ensure robust operation under both clear sky and rainy conditions, we propose a novel power-control scheme which applies an adaptive neuro-fuzzy inference system (ANFIS) for downlink CDMA-based LMDS systems. In the proposed system, the rain rate and the number of users are two inputs of the fuzzy inference system, and output is defined as channel quality, which is applied in the power control scheme to adjust the power control region. Moreover, ITU-R P.530 is employed to estimate the rain attenuation. The influence of the rain rate and the number of users on the distance-based power control (DBPC) scheme is included in the simulation model as the training database. Simulation results indicate that the proposed scheme improves the throughput of the DBPC scheme.

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TFNM, ANN, ANFIS를 이용한 국가지하수관측망 지하수위 변동 예측 비교 연구 (A Comparative Study on Forecasting Groundwater Level Fluctuations of National Groundwater Monitoring Networks using TFNM, ANN, and ANFIS)

  • 윤필선;윤희성;김용철;김규범
    • 한국지하수토양환경학회지:지하수토양환경
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    • 제19권3호
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    • pp.123-133
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    • 2014
  • It is important to predict the groundwater level fluctuation for effective management of groundwater monitoring system and groundwater resources. In the present study, three different time series models for the prediction of groundwater level in response to rainfall were built, those are transfer function noise model (TFNM), artificial neural network (ANN), and adaptive neuro fuzzy interference system (ANFIS). The models were applied to time series data of Boen, Cheolsan, and Hongcheon stations in National Groundwater Monitoring Network. The result shows that the model performance of ANN and ANFIS was higher than that of TFNM for the present case study. As lead time increased, prediction accuracy decreased with underestimation of peak values. The performance of the three models at Boen station was worst especially for TFNM, where the correlation between rainfall and groundwater data was lowest and the groundwater extraction is expected on account of agricultural activities. The sensitivity analysis for the input structure showed that ANFIS was most sensitive to input data combinations. It is expected that the time series model approach and results of the present study are meaningful and useful for the effective management of monitoring stations and groundwater resources.

Reliability analysis of an embedded system with multiple vacations and standby

  • Sharma, Richa;Kaushik, Manju;Kumar, Gireesh
    • International Journal of Reliability and Applications
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    • 제16권1호
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    • pp.35-53
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    • 2015
  • This investigation deals with reliability and sensitivity analysis of a repairable embedded system with standby wherein repairman takes multiple vacations. The hardware system consists of 'M' operating and 'S' standby components. The repairman can leave for multiple vacations of random length during its idle time. Whenever any operating unit fails, it is immediately replaced by a standby unit if available. Moreover, governing equations of an embedded system are constructed using appropriate birth-death rates. The vacation and repair time of repairman are exponentially distributed. The matrix method is used to find the steady-state probabilities of the number of failed components in the embedded system as well as other performance measures. Reliability indexes are presented. Further, numerical experiments are carried out for various system characteristics to examine the effects of different parameter. Using a special class of neuro-fuzzy systems i.e. Adaptive Network-based Fuzzy Interference Systems (ANFIS), we also approximate various performance measures. Finally, the conclusions and future research directions are provided.