• Title/Summary/Keyword: mean squared error (MSE)

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Developing drilling rate index prediction: A comparative study of RVR-IWO and RVR-SFL models for rock excavation projects

  • Hadi Fattahi;Nasim Bayat
    • Geomechanics and Engineering
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    • v.36 no.2
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    • pp.111-119
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    • 2024
  • In the realm of rock excavation projects, precise estimation of the drilling rate index stands as a pivotal factor in strategic planning and cost assessment. This study introduces and evaluates two pioneering computational intelligence models designed for the prognostication of the drilling rate index, a pivotal parameter with direct implications for cost estimation in rock excavation projects. These models, denoted as the Relevance Vector Regression (RVR) optimized with the Invasive Weed Optimization algorithm (IWO) (RVR-IWO model) and the RVR integrated with the Shuffled Frog Leaping algorithm (SFL) (RVR-SFL model), represent a groundbreaking approach to forecasting drilling rate index. The RVR-IWO and RVR-SFL models were meticulously devised to harness the capabilities of computational intelligence and optimization techniques for drilling rate index estimation. This research pioneers the integration of IWO and SFL with RVR, constituting an unprecedented effort in forecasting drilling rate index. The primary objective of this study was to gauge the precision and dependability of these models in forecasting the drilling rate index, revealing significant distinctions between the two. In terms of predictive precision, the RVR-IWO model emerged as the superior choice when compared to the RVR-SFL model, underscoring the remarkable efficacy of the Invasive Weed Optimization algorithm. The RVR-IWO model delivered noteworthy results, boasting a Variance Account for (VAF) of 0.8406, a Mean Squared Error (MSE) of 0.0114, and a Squared Correlation Coefficient (R2) of 0.9315. On the contrary, the RVR-SFL model exhibited slightly lower precision, yielding an MSE of 0.0160, a VAF of 0.8205, and an R2 of 0.9120. These findings serve to highlight the potential of the RVR-IWO model as a formidable instrument for drilling rate index prediction, particularly within the framework of rock excavation projects. This research not only makes a significant contribution to the realm of drilling engineering but also underscores the broader adaptability of the RVR-IWO model in tackling an array of challenges within the domain of rock engineering. Ultimately, this study advances the comprehension of drilling rate index estimation and imparts valuable insights into the practical implementation of computational intelligence methodologies within the realm of engineering projects.

Sparse Signal Recovery with Parallel Orthogonal Matching Pursuit for Multiple Measurement Vectors (병렬OMP 기법을 통한 복수 측정 벡터기반 성긴 신호의 복원)

  • Park, Jeonghong;Ban, Tae Won;Jung, Bang Chul
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.17 no.10
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    • pp.2252-2258
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    • 2013
  • In this paper, parallel orthogonal matching pursuit (POMP) is proposed to supplement the simultaneous orthogonal matching pursuit (S-OMP) which has been widely used as a greedy algorithm for sparse signal recovery for multiple measurement vector (MMV) problem. The process of POMP is simple but effective: (1) multiple indexes maximally correlated with the observation vector are chosen at the first iteration, (2) the conventional S-OMP process is carried out in parallel for each selected index, (3) the index set which yields the minimum residual is selected for reconstructing the original sparse signal. Empirical simulations show that POMP for MMV outperforms than the conventional S-OMP both in terms of exact recovery ratio (ERR) and mean-squared error (MSE).

A Channel Estimation Method for Multipath Feedback Interference Signal Cancellation of RF Repeaters (RF 중계기의 다중 궤환 간섭 신호 제거를 위한 채널 추정 방식)

  • Lee, Sang-Dae;Park, Jin;Sung, Won-Jin
    • The Journal of Korean Institute of Communications and Information Sciences
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    • v.33 no.2A
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    • pp.98-106
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    • 2008
  • To reduce the outage probability and to increase the transmission capacity, the importance of repeaters in cellular systems keeps increasing. Unlike optical repeaters which require wireline connections, RF repeaters are easy to install, have low limitations in location and also have a reduced operational expense such as the optical fiber maintenance cost. On the other hand, RF repeaters suffer the interference due to the feedback signals between the transmitter and receiver antennas, hence require an extra interference cancellation method when the amount of the feedback signal reduction by using the shielding is not sufficient. In this paper, a channel estimation method for two-path feedback interference signals in the ICS (Interference Cancellation System) repeaters using baseband signal processing is proposed and its performance is evaluated. When compared with the conventional method which estimates each multipath individually, the proposed method achieves 10 dB performance gain in terms of the normalized mean-squared-error.

Analysis on Optimal Approach of Blind Deconvolution Algorithm in Chest CT Imaging (흉부 컴퓨터단층촬영 영상에서 블라인드 디컨볼루션 알고리즘 최적화 방법에 대한 연구)

  • Lee, Young-Jun;Min, Jung-Whan
    • Journal of radiological science and technology
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    • v.45 no.2
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    • pp.145-150
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    • 2022
  • The main purpose of this work was to restore the blurry chest CT images by applying a blind deconvolution algorithm. In general, image restoration is the procedure of improving the degraded image to get the true or original image. In this regard, we focused on a blind deblurring approach with chest CT imaging by using digital image processing in MATLAB, which the blind deconvolution technique performed without any whole knowledge or information as to the fundamental point spread function (PSF). For our approach, we acquired 30 chest CT images from the public source and applied three type's PSFs for finding the true image and the original PSF. The observed image might be convolved with an isotropic gaussian PSF or motion blurring PSF and the original image. The PSFs are assumed as a black box, hence restoring the image is called blind deconvolution. For the 30 iteration times, we analyzed diverse sizes of the PSF and tried to approximate the true PSF and the original image. For improving the ringing effect, we employed the weighted function by using the sobel filter. The results was compared with the three criteria including mean squared error (MSE), root mean squared error (RMSE) and peak signal-to-noise ratio (PSNR), which all values of the optimal-sized image outperformed those that the other reconstructed two-sized images. Therefore, we improved the blurring chest CT image by using the blind deconvolutin algorithm for optimal approach.

Directed Graph를 이용한 경제 모형의 접근 - Crandall의 탑승자 사망 모형에 관한 수정- ( Directed Graphical Approach for Economic Modeling : A Revision of Crandall's Occupant Death Model )

  • Roh, J.W.
    • Journal of Korean Port Research
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    • v.12 no.1
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    • pp.55-64
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    • 1998
  • Directed graphic algorithm was applied to an empirical analysis of traffic occupant fatalities based on a model by Crandall. In this paper, Crandall's data on U.S. traffic fatalities for the period 1947-1981 are focused and extended to include 1982-1993. Based on the 1947-1981 annual data, the directed graph algorithms reveal that occupant traffic deaths are directly caused by income, vehicle miles, and safety devices. Vehicle mileage is caused by income and rural driving. The estimation is conducted using three stage least squares regression. Those results show a difference between the traditional regression methodology and causal graphical analysis. It is also found that forecasts from the directed graph based model outperform forecasts from the regression-based models, in terms of mean squared forecasts error. Furthermore, it is demonstrates that there exists some latent variables between all explanatory variables and occupant deaths.

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How to Set an Appropriate Scale of Traffic Analysis Zone for Estimating Travel Patterns of E-Scooter in Transporation Planning? (전동킥보드 통행분포모형 추정을 위한 적정 존단위 선정 연구)

  • Kyu hyuk Kim;Sang hoon Kim;Tai jin Song
    • The Journal of The Korea Institute of Intelligent Transport Systems
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    • v.22 no.3
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    • pp.51-61
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    • 2023
  • Travel demand estimation of E-Scooter is the start point of solving the regional demand-supply imbalance problem and plays pivotal role in a linked transportation system such as Mobility-as-a-Service (a.k.a. MaaS). Most focuses on developing trip generation model of shared E-Scooter but it is no study on selection of an appropriate zone scale when it comes to estimating travel demand of E-Scooter. This paper aimed for selecting an optimal TAZ scale for developing trip distribution model for shared E-Scooter. The TAZ scale candidates were selected in 250m, 500m, 750m, 1,000m square grid. The shared E-Scooter usage historical data were utilized for calculating trip distance and time, and then applying to developing gravity model. Mean Squared Error (MSE) is applied for the verification step to select the best suitable gravity model by TAZ scale. As a result, 250m of TAZ scale is the best for describing practical trip distribution of shared E-Scooter among the candidates.

Parameter Estimation and Comparison for SRGMs and ARIMA Model in Software Failure Data

  • Song, Kwang Yoon;Chang, In Hong;Lee, Dong Su
    • Journal of Integrative Natural Science
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    • v.7 no.3
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    • pp.193-199
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    • 2014
  • As the requirement on the quality of the system has increased, the reliability is very important part in terms of enhance stability and to provide high quality services to customers. Many statistical models have been developed in the past years for the estimation of software reliability. We consider the functions for NHPP software reliability model and time series model in software failure data. We estimate parameters for the proposed models from three data sets. The values of SSE and MSE is presented from three data sets. We compare the predicted number of faults with the actual three data sets using the NHPP software reliability model and time series model.

Signal Processing for Perpendicular Recording Systems

  • Lee, Jun;Woo, Choong-Chae
    • Journal of IKEEE
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    • v.15 no.1
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    • pp.70-75
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    • 2011
  • Longitudinal recording has been the cornerstone of all two generations of magnetic recording systems, FDD and HDD. In recent, perpendicular recording has received much attention as promising technology for future high-density recording system Research into signal processing techniques is paramount for the issued storage system and is indispensable like longitudinal recording systems. This paper focuses on the performance evaluation of the various detectors under perpendicular recording system. Parameters for improving the their performance are examined for some detectors. Detectors considered in this work are the partial response maximum likelihood (PRML), noise-predictive maximum likelihood (NPML), fixed delay tree search with decision feedback (FDTS/DF), dual decision feedback equalizer (DDFE) and multilevel decision feedback equalizer (MDFE). Their performances are analyzed in terms of mean squared error (MSE) and noise power spectra, and similarity between recording channel and partial response (PR) channel.

Time Delay Estimation using Third-order Statistics and Subband Adaptive Filtering (3차 통계기법과 서브밴드 적응 필터링을 이용한 시간 지연 추정)

  • 박현석;남상원
    • Proceedings of the IEEK Conference
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    • 2001.09a
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    • pp.907-910
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    • 2001
  • In this paper, we address a new time delay estimation method using third-order statistics and subband adaptive filtering to improve the accuracy of target detection for acoustic backscattered signals in a noise interference environment. Each reference and primary signals are decorrelated using the multiresolution analysis framework through a M-band discrete wavelet transform(M-DWT). Then noise effect can be reduced. Here, time delays are estimated iteratively in each subband using two different adaptation mechanisms that minimize the mean squared error (MSE) between the references and primary signal. More specifically, third-order cumulants and projection cross-correlation(PCC) criterion are utilized to achieve an effective SNR improvement for the time delay estimation.

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Bayesian Inference for Multinomial Group Testing

  • Heo, Tae-Young;Kim, Jong-Min
    • Communications for Statistical Applications and Methods
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    • v.14 no.1
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    • pp.81-92
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    • 2007
  • This paper consider trinomial group testing concerned with classification of N given units into one of k disjoint categories. In this paper, we propose Bayesian inference for estimating individual category proportions using the trinomial group testing model proposed by Bar-Lev et al. (2005). We compared a relative efficience (RE) based on the mean squared error (MSE) of MLE and Bayes estimators with various prior information. The impact of different prior specifications on the estimates is also investigated using selected prior distribution. The impact of different priors on the Bayes estimates is modest when the sample size and group size we large.