scholarly journals New formulations for prediction of velocity at limit of deposition in storm sewers based on a stochastic technique

2020 ◽  
Vol 81 (12) ◽  
pp. 2634-2649
Author(s):  
Ali Tafarojnoruz ◽  
Ahmad Sharafati
Keyword(s):  
Performance Improvement ◽  
Performance Indices ◽  
Densimetric Froude Number ◽  
Sewer Pipes ◽  
Research Findings ◽  
Generalized Likelihood Uncertainty Estimation ◽  
Two Parameter ◽  
Improvement Index ◽  
Conventional Regression ◽  
Storm Sewers

Abstract Sedimentation in storm sewers strongly depends on velocity at limit of deposition. This study provides application of a novel stochastic-based model to predict the densimetric Froude number in sewer pipes. In this way, the generalized likelihood uncertainty estimation (GLUE) is used to develop two parametric equations, called GLUE-based four-parameter and GLUE-based two-parameter (GBTP) models to enhance the prediction accuracy of the velocity at the limit of deposition. A number of performance indices are calculated in training and testing phases to compare the developed models with the conventional regression-based equations available in the literature. Based on the obtained performance indices and some graphical techniques, the research findings confirm that a significant enhancement in prediction performance is achieved through the proposed GBTP compared with the previously developed formulas in the literature. To make a quantified comparison between the established and literature models, an index, called improvement index (IM), is computed. This index is a resultant of all the selected indices, and this indicator demonstrates that GBTP is capable of providing the most performance improvement in both training () and testing () phases, comparing with a well-known formula in this context.

scholarly journals New stochastic modeling strategy on the prediction enhancement of pier scour depth in cohesive bed materials

2020 ◽  
Vol 22 (3) ◽  
pp. 457-472 ◽  
Author(s):  
Ahmad Sharafati ◽  
Ali Tafarojnoruz ◽  
Zaher Mundher Yaseen
Keyword(s):  
Group Method ◽  
Scour Depth ◽  
Cohesive Soils ◽  
Reliable Prediction ◽  
Pier Scour ◽  
Bed Materials ◽  
Modeling Strategy ◽  
Generalized Likelihood Uncertainty Estimation ◽  
Cohesive Bed ◽  
Improvement Index

Abstract Scouring around the piers, especially in cohesive bed materials, is a fully stochastic phenomenon and a reliable prediction of scour depth is still a challenging concern for bridge designers. This study introduces a new stochastic model based on the integration of Group Method of Data Handling (GMDH) and Generalized Likelihood Uncertainty Estimation (GLUE) to predict scour depth around piers in cohesive soils. The GLUE approach is developed to estimate the related parameters whereas the GMDH model is used for the prediction target. To assess the adequacy of the GMDH-GLUE model, the conventional GMDH and genetic programming (GP) models are also developed for evaluation. Several statistical performance indicators are computed over both the training and testing phases for the prediction accuracy validation. Based on the attained numerical indicators, the proposed GMDH-GLUE model revealed better predictability performance of pier scour depth against the benchmark models as well as several gathered literature studies. To provide an informative comparison among the proposed techniques (i.e. GMDH-GLUE, GMDH, and GP models), an improvement index () is employed. Results indicated that the GMDH-GLUE model achieved = 6% and = 3%, demonstrating satisfying performance improvement in comparison with the previously proposed GMDH model.

USER AUTHENTICATION USING FUSION OF FACE AND PALMPRINT

2009 ◽  
Vol 09 (02) ◽  
pp. 251-270 ◽  
Author(s):  
AJAY KUMAR ◽  
DAVID ZHANG
Keyword(s):  
Performance Improvement ◽  
User Authentication ◽  
Digital Camera ◽  
Performance Indices ◽  
Feed Forward Neural Network ◽  
Class Separation ◽  
Criterion Functions ◽  
Significant Performance ◽  
Authentication System ◽  
Personal Authentication

This paper presents a new method of personal authentication using face and palmprint images. The facial and palmprint images can be simultaneously acquired by using a pair of digital camera and integrated to achieve higher confidence in personal authentication. The proposed method of fusion uses a feed-forward neural network to integrate individual matching scores and generate a combined decision score. The significance of the proposed method is more than improving performance for bimodal system. Our method uses the claimed identity of users as a feature for fusion. Thus the required weights and bias on individual biometric matching scores are automatically computed to achieve the best possible performance. The experimental results also demonstrate that Sum, Max, and Product rule can be used to achieve significant performance improvement when consolidated matching scores are employed instead of direct matching scores. The fusion strategy used in this paper outperforms even its existing facial and palmprint modules. The performance indices for personal authentication system using two-class separation criterion functions have been analyzed and evaluated. The method proposed in this paper can be extended for any multimodal authentication system to achieve higher performance.

scholarly journals Use of Derivative and Firm Performance: Evidence from the Chinese Shenzhen Stock Exchange

2021 ◽  
Vol 14 (2) ◽  
pp. 83
Author(s):  
Yantao Wen ◽  
Yuanfei Kang ◽  
Yafeng Qin ◽  
Jeffrey C. Kennedy
Keyword(s):  
Firm Performance ◽  
Performance Improvement ◽  
Stock Exchange ◽  
Financial Derivatives ◽  
Financial Risks ◽  
Firm Level ◽  
Listed Firms ◽  
Tax Shield ◽  
Negative Effect ◽  
Research Findings

Financial derivatives have been increasingly used by firms to hedge against financial risks. However, it is still not clear what factors at the firm level lead to firms’ derivative use and whether derivative use can generate performance improvement, especially in the context of firms operating in emerging economies. Using the unbalanced panel data consisting of 2529 listed firms from China covering an 11-year period from 2005 to 2015, this study examines these two questions regarding firms’ use of financial derivatives. Based on results from the empirical analysis, this study identified operational cash flow, tax shield, R&D investment, and the possibility of bankruptcy, as the firm-level factors that enable firms’ decision to invest in financial derivatives. More importantly, empirical findings from this study suggest that a firm’s derivative use tends to negatively affect firm performance, rather than improve firm performance. The negative effect of derivative use on firm performance is not consistent between the two groups of the better performer and poorer performer firms. While the poorly performed firms are more likely to use financial derivatives for the purpose of performance improvement, their derivative use tends to further damage, rather than improve, performance. These research findings have theoretical and practical implications.

scholarly journals Performance measurement indices for simulated construction operations

2001 ◽  
Vol 28 (3) ◽  
pp. 383-393 ◽  
Author(s):  
Brenda McCabe ◽  
Simaan M AbouRizk
Keyword(s):  
Artificial Intelligence ◽  
Computer Simulation ◽  
Performance Improvement ◽  
Belief Networks ◽  
Remedial Action ◽  
Performance Indices ◽  
Construction Operations ◽  
Construction Engineering ◽  
Simulation Performance ◽  
Acceptable Range

This paper describes the development of indices useful in automating the experimentation process of a computer simulation. Simulation methodologies have been developed to model construction systems, but most of these systems require the experimentation process to be carried out manually. In achieving optimum performance, one has to repeat an exhaustive number of experiments. The indices can be used to automate this process, as they are indicators of bottlenecks in the system that can be tracked through the simulation output. They are based upon user-defined performance guidelines for the resources. Where a performance index falls outside the acceptable range, remedial action may be taken. Belief networks, a probabilistic form of artificial intelligence, were used to automate the analysis of the indices to determine the most likely causal factor of poor performance.Key words: construction engineering, computer simulation, performance indices, belief networks, performance improvement.

Performance Calculation and Test Analysis of PDM Lining with Super-Elastic Constitutive Model

2013 ◽  
Vol 307 ◽  
pp. 139-143
Author(s):  
Jia Lin Tian ◽  
Rong Ming Hao ◽  
Lin Yang ◽  
Xin Wang ◽  
Zhe Fan ◽  
...  
Keyword(s):  
Performance Improvement ◽  
Rotation Speed ◽  
Performance Comparison ◽  
Test Analysis ◽  
Material Parameters ◽  
Overall Efficiency ◽  
And Performance ◽  
Performance Calculation ◽  
Two Parameter ◽  
Optimization And Performance

Based on performance comparison of PDM equidistant and conventional elastomer lining, the impacts on the PDM performance were presented with different equidistant lining thickness. According to the Mooney-Rivlin two-parameter model and the Poisson radio equaling to 0.5, the elastomer is incompressible during the calculation and its relational material parameters such as elastic modulus and shear modulus were determined. The PDM stator and rotor curve equations were established according to hypocycloid theory. The lobe configuration is 3:4, the performance comparisons were investigated including deformation and Mises stress between conventional and equidistant elastomer lining of PDM with contact model. The test data pointed out torque, rotation speed, volumetric and overall efficiency variation results with the motor pressure difference changing from 1.93MPa to 5.90MPa. The presented results could be used for PDM design optimization and performance improvement.

scholarly journals Decision tree (DT), generalized regression neural network (GR) and multivariate adaptive regression splines (MARS) models for sediment transport in sewer pipes

2019 ◽  
Vol 79 (6) ◽  
pp. 1113-1122 ◽  
Author(s):  
Mir Jafar Sadegh Safari
Keyword(s):  
Sediment Transport ◽  
Regression Models ◽  
Multivariate Adaptive Regression Splines ◽  
Generalized Regression Neural Network ◽  
Deposition Condition ◽  
Regression Splines ◽  
Sewer Pipes ◽  
Adaptive Regression ◽  
Adaptive Regression Splines ◽  
Conventional Regression

Abstract Sediment deposition in sewers and urban drainage systems has great effect on the hydraulic capacity of the channel. In this respect, the self-cleansing concept has been widely used for sewers and urban drainage systems design. This study investigates the bed load sediment transport in sewer pipes with particular reference to the non-deposition condition in clean bed channels. Four data sets available in the literature covering wide ranges of pipe size, sediment size and sediment volumetric concentration have been utilized through applying decision tree (DT), generalized regression neural network (GR) and multivariate adaptive regression splines (MARS) techniques for modeling. The developed models have been compared with conventional regression models available in the literature. The model performance indicators, showed that DT, GR and MARS models outperform conventional regression models. Result shows that GR and MARS models are comparable in terms of calculating particle Froude number and performing better than DT. It is concluded that conventional regression models generally overestimate particle Froude number for the non-deposition condition of sediment transport, while DT, GR and MARS outputs are close to their measured counterparts.

A support vector regression-firefly algorithm-based model for limiting velocity prediction in sewer pipes

2016 ◽  
Vol 73 (9) ◽  
pp. 2244-2250 ◽  
Author(s):  
Isa Ebtehaj ◽  
Hossein Bonakdari
Keyword(s):  
Support Vector Regression ◽  
Firefly Algorithm ◽  
Superior Performance ◽  
Percentage Error ◽  
Support Vector ◽  
Effective Parameters ◽  
Densimetric Froude Number ◽  
Sewer Pipes ◽  
Median Diameter ◽  
Velocity Prediction

Sediment transport without deposition is an essential consideration in the optimum design of sewer pipes. In this study, a novel method based on a combination of support vector regression (SVR) and the firefly algorithm (FFA) is proposed to predict the minimum velocity required to avoid sediment settling in pipe channels, which is expressed as the densimetric Froude number (Fr). The efficiency of support vector machine (SVM) models depends on the suitable selection of SVM parameters. In this particular study, FFA is used by determining these SVM parameters. The actual effective parameters on Fr calculation are generally identified by employing dimensional analysis. The different dimensionless variables along with the models are introduced. The best performance is attributed to the model that employs the sediment volumetric concentration (CV), ratio of relative median diameter of particles to hydraulic radius (d/R), dimensionless particle number (Dgr) and overall sediment friction factor (λs) parameters to estimate Fr. The performance of the SVR-FFA model is compared with genetic programming, artificial neural network and existing regression-based equations. The results indicate the superior performance of SVR-FFA (mean absolute percentage error = 2.123%; root mean square error =0.116) compared with other methods.

scholarly journals Efficient statistics-based algebraic codebook search algorithms derived from RCM for an ACELP speech coder

2015 ◽  
Vol 44 (4) ◽  
pp. 410-419
Author(s):  
Tzu-Hung Lin ◽  
Cheng-Yu Yeh ◽  
Shaw-Hwa Hwang
Keyword(s):  
Performance Improvement ◽  
Search Algorithms ◽  
Speech Quality ◽  
Search Performance ◽  
Major Research ◽  
First Finding ◽  
High Contribution ◽  
Research Findings ◽  
Algebraic Code ◽  
Speech Coder

Applied to analgebraic codebook search conducted on an algebraic code-excitedlinear-prediction (ACELP) speech coder, two improved versions of reducedcandidate mechanism (RCM), designated as Fixed-G1-RCM and Fixed-2Track-RCM, arepresented in this study for further search performance improvement. It ismainly derived from two major research findings in a piece of our prior work.The first finding is that a pulse with a high contribution in a track is morelikely to serve as the optimal pulse in the optimal vector pertaining to thetrack, and the second is that the speech quality can be well maintained at asearch accuracy above 50%. In this proposal, the trade off can be tuned betweenthe search accuracy and the search complexity so as to reach a nearlyconsistent speech quality. It is experimentally demonstrated that either Fixed-G1-RCM(N = 3), or Fixed-2Track-RCM (M = 2, N = 3, or M = 3, N = 4) can provide ahighly superior search performance relative to a global pulse replacementmethod (iteration = 2) and an iteration-freepulse replacement method.DOI: http://dx.doi.org/10.5755/j01.itc.44.4.9847

scholarly journals An exploration on e-retailers’ home delivery – strategic elements and their prioritisation

2016 ◽  
Vol 22 (3) ◽  
pp. 614-633 ◽  
Author(s):  
Chengbo Wang ◽  
Zhaofang Mao ◽  
James O'Kane ◽  
Jun Wang
Keyword(s):  
Performance Improvement ◽  
Home Delivery ◽  
Strategy Development ◽  
Global Marketplace ◽  
Content Type ◽  
Delivery Performance ◽  
Retail Strategy ◽  
Research Findings ◽  
Logistics Process ◽  
Practical Implications

Purpose – The purpose of this paper is to introduce a research exploring the important strategic elements and their prioritisation for e-retailers’ home delivery logistics process efficacy improvement. Design/methodology/approach – The research was completed through focus group, survey and importance-performance analysis. Findings – The research identified, confirmed and prioritised a set of explicitly important strategic elements currently deemed important by e-retailers for ensuring the efficacy of their home delivery logistics process in Chinese marketplace, and also referential to the other similar emerging marketplaces. Research limitations/implications – The research contributes positively to the enrichment of the theoretical knowledge pool of e-retailers’ logistics performance improvement. Practical implications – The research findings guide/inform the strategy development and implementation for e-retailers entering and/or operating in Chinese marketplace. And the findings can also be referential to the e-retail strategy development for entering and operating in other emerging markets similar to China’s. This point is particularly meaningful for those e-retailers that want to expand the outreaching and increase the popularity of their businesses in the global marketplace. Originality/value – Corresponding to the much needed further research on e-retailing home delivery performance improvement, the research provides findings that add substantial new insights into the field, with a particular focus on China, as one of the emerging developing marketplaces.

Factors contributing to non-value adding activities in South African construction

2014 ◽  
Vol 12 (2) ◽  
pp. 223-243 ◽  
Author(s):  
Fidelis Emuze ◽  
John Smallwood ◽  
Sangwon Han
Keyword(s):  
South Africa ◽  
Public Sector ◽  
South African ◽  
Performance Improvement ◽  
Design Methodology ◽  
Poor Performance ◽  
Project Performance ◽  
Content Type ◽  
Qualitative Models ◽  
Research Findings

Purpose – Non-value adding activities (NVAAs) are considered to be problematic in the management of projects. Reported research findings suggest that these NVAAs consume resources without necessarily adding value to completed tasks. The main aim of the research is to provide insights and plausible explanations concerning how NVAAs can propagate poor performance in South Africa. Design/methodology/approach – The paper reports on a quantitative survey conducted among public sector clients, consulting engineers, and civil engineering contractors in South Africa. Using a framework that was developed from the literature reviewed, the study proposed three conceptual qualitative models that were based on system dynamics. Findings – The study suggests that NVAAs that are prevalent in South African construction can impact project performance negatively in the form of cost and time overruns. It can also be argued that although there is commonality between NVAAs that are identified in South Africa and other countries, their frequency and effects on project performance differ. Research limitations/implications – The findings provide further insights about NVAAs that are related to the South African infrastructure sector only. Originality/value – The study, which is the first of such in South Africa, could lead to increased awareness among South African project stakeholders that are concerned about performance improvement from the lean construction perspective.

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