scholarly journals Energy Loss in Skimming Flow over Cascade Spillways: Comparison of Artificial Intelligence-Based and Regression Methods

2020 ◽  
Vol 10 (19) ◽  
pp. 6903
Author(s):  
Meysam Nouri ◽  
Parveen Sihag ◽  
Farzin Salmasi ◽  
Ozgur Kisi
Keyword(s):  
Artificial Intelligence ◽  
Energy Dissipation ◽  
Laboratory Experiments ◽  
Relative Energy ◽  
Hydraulic Parameters ◽  
Regression Methods ◽  
Input And Output ◽  
Analysis Theory ◽  
Wide Range ◽  
Input Variables

In this study, the energy dissipation of cascade spillways was studied by conducting a series of laboratory experiments. Five spillways slope angles (α) (10°, 20°, 30°, 40°, and 50°), various step numbers (N) ranging from 4 to 75, and a wide range of discharges (Q), were considered. Some data-based models were developed to explain the relationships between hydraulic parameters. Multiple linear and nonlinear regression-based equations were developed based on dimensional analysis theory to compute energy dissipation over cascade spillways. For testing the robustness of developed data-based models, M5P, stochastic M5P, and random forest (RF) were used as new artificial intelligence (AI)-based techniques. To relate the input and output variables of energy dissipation, AI-based and regression approaches were developed. It was found that the formulation based on the stochastic M5P approach in solving energy dissipation problems over cascade spillways is more successful than the other regression and AI-based methods. Sensitivity analysis suggests that spillway slope in degrees (α) is the most influential input variable in predicting the relative energy dissipation (%) of the spillway in comparison to other input variables.

scholarly journals A Model To Estimate Firms Accounting-Based Performance: A Data Envelopment Approach

2014 ◽  
Vol 13 (6) ◽  
pp. 1301 ◽  
Author(s):  
Merwe Oberholzer
Keyword(s):  
Weighted Average ◽  
Data Envelopment ◽  
Accounting Data ◽  
Dea Model ◽  
Analytical Reasoning ◽  
Input And Output ◽  
Analysis Theory ◽  
Net Profit ◽  
Optimal Capital ◽  
Input Variables

The objective of the study was to follow a logical inductive approach to develop a Data Envelopment Analysis (DEA) model to estimate the relative technical efficiency of firms. The Du Pont analysis theory as conceptual framework was applied using primarily readily available accounting line-items as input and output variables. From an interpretive epistemological paradigm and analytical reasoning, a new DEA model was developed with Weighted Average Cost of Capital (WACC), leverage and expenditure as input variables and revenue, net profit and Earnings Before Interest, Tax, Depreciation and Amortization (EBITDA) as output variables. The originality of this study is that this is the first effort to employ accounting data, based on the Du Pont analysis in a DEA model. All the input and output variables in the model were already used individually or in combinations by previous studies, except for WACC. The study argues that WACC should be employed as a proxy for the accounting line-items, equity and liabilities, since lowering WACC implies that firms are moving closer to their optimal capital structures.

scholarly journals Soft Computing Predictions of Relative Energy Dissipation for Vertical Drops Equipped with a Horizontal Screen

2020 ◽  
Author(s):  
Reza Norouzi ◽  
Rasoul Daneshfaraz ◽  
John Abraham ◽  
Parveen Sihag
Keyword(s):  
Energy Dissipation ◽  
Linear Regression ◽  
Regression Model ◽  
Linear Regression Model ◽  
Multiple Linear Regression Model ◽  
Absolute Error ◽  
Sensitivity Study ◽  
Relative Energy ◽  
Study Results ◽  
Input Variables

Drops are the most important and most common energy dissipator in irrigation networks and erodible canals and consequently, their performance must be well understood. This study was designed to evaluate the capability of Artificial Intelligence (AI) methods including ANN, ANFIS, GRNN, SVM, GP, MLR, and LR to predict the relative energy dissipation (∆E/E0) in vertical drops equipped with a horizontal screen. For this study, 108 experiments were carried out to investigate energy dissipation with variable discharge, varying drop height, and porosity of the horizontal screens. Parameters yc/h, yd/yc, and p are considered as input variables and ∆E/E0 is the output variable. The efficiency of models was compared using Taylor's diagram, Box Plot of the applied error distribution, correlation coefficient (CC), mean absolute error (MAE) and root-mean-square error (RMSE). Results indicate that the performance of the ANFIS_gbellmf based model with CC value of 0.9953, RMSE value of 0.0069 and MAE value of 0.0042 was superior to other applied models. Also, the linear regression model with CC=0.9933, RMSE=0.0083, and MAE= 0.0067performs better than the multiple linear regression model in this study. Results of a sensitivity study suggest that yc/h is the most effective parameter for predicting ∆E/E0.

scholarly journals Predictive modelling of soils’ hydraulic conductivity using artificial neural network and multiple linear regression

2021 ◽  
Vol 3 (2) ◽  
Author(s):  
Charles Gbenga Williams ◽  
Oluwapelumi O. Ojuri
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Hydraulic Conductivity ◽  
Linear Regression ◽  
Multiple Linear Regression ◽  
Coarse Grained ◽  
Soil Types ◽  
Wide Range ◽  
Artificial Neural ◽  
Input Variables

AbstractAs a result of heterogeneity nature of soils and variation in its hydraulic conductivity over several orders of magnitude for various soil types from fine-grained to coarse-grained soils, predictive methods to estimate hydraulic conductivity of soils from properties considered more easily obtainable have now been given an appropriate consideration. This study evaluates the performance of artificial neural network (ANN) being one of the popular computational intelligence techniques in predicting hydraulic conductivity of wide range of soil types and compared with the traditional multiple linear regression (MLR). ANN and MLR models were developed using six input variables. Results revealed that only three input variables were statistically significant in MLR model development. Performance evaluations of the developed models using determination coefficient and mean square error show that the prediction capability of ANN is far better than MLR. In addition, comparative study with available existing models shows that the developed ANN and MLR in this study performed relatively better.

Observations of Small-Scale Turbulence and Energy Dissipation Rates in the Cloudy Boundary Layer

2006 ◽  
Vol 63 (5) ◽  
pp. 1451-1466 ◽  
Author(s):  
Holger Siebert ◽  
Katrin Lehmann ◽  
Manfred Wendisch
Keyword(s):  
Boundary Layer ◽  
Energy Dissipation ◽  
Wind Velocity ◽  
Turbulence Theory ◽  
Horizontal Wind ◽  
Inertial Subrange ◽  
Intermittent Flow ◽  
Small Scale ◽  
Dissipation Rates ◽  
Wide Range

Abstract Tethered balloon–borne measurements with a resolution in the order of 10 cm in a cloudy boundary layer are presented. Two examples sampled under different conditions concerning the clouds' stage of life are discussed. The hypothesis tested here is that basic ideas of classical turbulence theory in boundary layer clouds are valid even to the decimeter scale. Power spectral densities S( f ) of air temperature, liquid water content, and wind velocity components show an inertial subrange behavior down to ≈20 cm. The mean energy dissipation rates are ∼10−3 m2 s−3 for both datasets. Estimated Taylor Reynolds numbers (Reλ) are ∼104, which indicates the turbulence is fully developed. The ratios between longitudinal and transversal S( f ) converge to a value close to 4/3, which is predicted by classical turbulence theory for local isotropic conditions. Probability density functions (PDFs) of wind velocity increments Δu are derived. The PDFs show significant deviations from a Gaussian distribution with longer tails typical for an intermittent flow. Local energy dissipation rates ɛτ are derived from subsequences with a duration of τ = 1 s. With a mean horizontal wind velocity of 8 m s−1, τ corresponds to a spatial scale of 8 m. The PDFs of ɛτ can be well approximated with a lognormal distribution that agrees with classical theory. Maximum values of ɛτ ≈ 10−1 m2 s−3 are found in the analyzed clouds. The consequences of this wide range of ɛτ values for particle–turbulence interaction are discussed.

scholarly journals Corporate Governance of Artificial Intelligence in the Public Interest

Information ◽  
2021 ◽  
Vol 12 (7) ◽  
pp. 275
Author(s):  
Peter Cihon ◽  
Jonas Schuett ◽  
Seth D. Baum
Keyword(s):  
Artificial Intelligence ◽  
Corporate Governance ◽  
Law Enforcement ◽  
Nonprofit Organizations ◽  
Public Interest ◽  
Department Of Defense ◽  
The Public ◽  
Wide Range ◽  
The Media ◽  
The U.S

Corporations play a major role in artificial intelligence (AI) research, development, and deployment, with profound consequences for society. This paper surveys opportunities to improve how corporations govern their AI activities so as to better advance the public interest. The paper focuses on the roles of and opportunities for a wide range of actors inside the corporation—managers, workers, and investors—and outside the corporation—corporate partners and competitors, industry consortia, nonprofit organizations, the public, the media, and governments. Whereas prior work on multistakeholder AI governance has proposed dedicated institutions to bring together diverse actors and stakeholders, this paper explores the opportunities they have even in the absence of dedicated multistakeholder institutions. The paper illustrates these opportunities with many cases, including the participation of Google in the U.S. Department of Defense Project Maven; the publication of potentially harmful AI research by OpenAI, with input from the Partnership on AI; and the sale of facial recognition technology to law enforcement by corporations including Amazon, IBM, and Microsoft. These and other cases demonstrate the wide range of mechanisms to advance AI corporate governance in the public interest, especially when diverse actors work together.

scholarly journals Optimising the AR Engraved Structure on Light-Guide Facets for a Wide Range of Wavelengths

Optics ◽  
2020 ◽  
Vol 2 (1) ◽  
pp. 25-42
Author(s):  
Ioseph Gurwich ◽  
Yakov Greenberg ◽  
Kobi Harush ◽  
Yarden Tzabari
Keyword(s):  
Theoretical Analysis ◽  
Light Guide ◽  
Spectral Band ◽  
Angular Range ◽  
The Past ◽  
Input And Output ◽  
Wide Range ◽  
The Given ◽  
Theoretical Results ◽  
Shape And Size

The present study is aimed at designing anti-reflective (AR) engraving on the input–output surfaces of a rectangular light-guide. We estimate AR efficiency, by the transmittance level in the angular range, determined by the light-guide. Using nano-engraving, we achieve a uniform high transmission over a wide range of wavelengths. In the past, we used smoothed conical pins or indentations on the faces of light-guide crystal as the engraved structure. Here, we widen the class of pins under consideration, following the physical model developed in the previous paper. We analyze the smoothed pyramidal pins with different base shapes. The possible effect of randomization of the pins parameters is also examined. The results obtained demonstrate optimized engraved structure with parameters depending on the required spectral range and facet format. The predicted level of transmittance is close to 99%, and its flatness (estimated by the standard deviation) in the required wavelengths range is 0.2%. The theoretical analysis and numerical calculations indicate that the obtained results demonstrate the best transmission (reflection) we can expect for a facet with the given shape and size for the required spectral band. The approach is equally useful for any other form and of the facet. We also discuss a simple way of comparing experimental and theoretical results for a light-guide with the designed input and output features. In this study, as well as in our previous work, we restrict ourselves to rectangular facets. We also consider the limitations on maximal transmission produced by the size and shape of the light-guide facets. The theoretical analysis is performed for an infinite structure and serves as an upper bound on the transmittance for smaller-size apertures.

CONVERGENCE IMPROVEMENT OF ADAPTIVE LATTICE ALGORITHM WITH FUZZY BASED ADAPTIVE GAIN

1999 ◽  
Vol 09 (01n02) ◽  
pp. 125-132
Author(s):  
GEUN-TAEK RYU ◽  
DAE-SUNG KIM ◽  
DAE-YOUNG LEE ◽  
SUNG-HWAN HAN ◽  
HYEON-DEOK BAE
Keyword(s):  
Adaptive Filters ◽  
Communication Channel ◽  
Long Distance ◽  
Input And Output ◽  
Forward Prediction ◽  
Adaptation Procedure ◽  
Distance Communication ◽  
One Step ◽  
Input Variables ◽  
Lattice Algorithm

The choice of the adaptive gain is important to the performance of LMS-based adaptive filters. Depending on application areas, the realization structure of the filters is also important. This letter presents an adaptive lattice algorithm which adjusts the adaptive gain of LMS using fuzzy if-then rules determined by matching input and output variables during adaptation procedure. In each lattice filter stage, this filter adjusts the adaptive gain as the output of the fuzzy logic which has two input variables, normalized squared forward prediction error and one step previous adaptive gain. The proposed algorithm is applied to echo canceling problem of long distance communication channel. The simulation results are compared with NLMS on TDL and lattice structures.

The Research and Application of Artificial Intelligence in the Field of Intelligent Robot

2014 ◽  
Vol 898 ◽  
pp. 763-766
Author(s):  
Zhi Hao Li
Keyword(s):  
Artificial Intelligence ◽  
Environmental Changes ◽  
Vision System ◽  
Mineral Exploration ◽  
Intelligent Robot ◽  
Application Range ◽  
Intelligent Robots ◽  
External Data ◽  
Wide Range ◽  
Artificial Intelligence Application

The research and application of artificial intelligence has a very wide range in intelligent robot field. Intelligent robot can not only make use of artificial intelligence gain access to external data, information, (such as stereo vision system, face recognition and tracking, etc.), and then deal with it so as to exactly describe external environment, and complete a task independently, owing the ability of learning knowledge, but also have self-many kinds of artificial intelligence like judgment and decision making, processing capacity and so on. It can make corresponding decision according to environmental changes. Its application range is expanding. In deep sea exploration, star exploration, mineral exploration, heavy pollution, domestic service, entertainment clubs, health care and so on, the figure of intelligent robots artificial intelligence application can all be seen.

APPLICATION OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN MS. PAC-MAN GAME: A REVIEW

2015 ◽  
Vol 3 (1) ◽  
Author(s):  
Tse Guan Tan ◽  
Jason Teo
Keyword(s):  
Artificial Intelligence ◽  
Content Analysis ◽  
Video Games ◽  
Analysis Method ◽  
Engineering Economics ◽  
Game Ai ◽  
Content Analysis Method ◽  
Wide Range ◽  
Computer Based ◽  
Future Direction

AbstrakTeknik Kecerdasan Buatan (AI) berjaya digunakan dan diaplikasikan dalam pelbagai bidang, termasukpembuatan, kejuruteraan, ekonomi, perubatan dan ketenteraan. Kebelakangan ini, terdapat minat yangsemakin meningkat dalam Permainan Kecerdasan Buatan atau permainan AI. Permainan AI merujukkepada teknik yang diaplikasikan dalam permainan komputer dan video seperti pembelajaran, pathfinding,perancangan, dan lain-lain bagi mewujudkan tingkah laku pintar dan autonomi kepada karakter dalampermainan. Objektif utama kajian ini adalah untuk mengemukakan beberapa teknik yang biasa digunakandalam merekabentuk dan mengawal karakter berasaskan komputer untuk permainan Ms Pac-Man antaratahun 2005-2012. Ms Pac-Man adalah salah satu permainan yang digunakan dalam siri pertandinganpermainan diperingkat antarabangsa sebagai penanda aras untuk perbandingan pengawal autonomi.Kaedah analisis kandungan yang menyeluruh dijalankan secara ulasan dan sorotan literatur secara kritikal.Dapatan kajian menunjukkan bahawa, walaupun terdapat berbagai teknik, limitasi utama dalam kajianterdahulu untuk mewujudkan karakter permaianan Pac Man adalah kekurangan Generalization Capabilitydalam kepelbagaian karakter permainan. Hasil kajian ini akan dapat digunakan oleh penyelidik untukmeningkatkan keupayaan Generalization AI karakter permainan dalam Pasaran Permainan KecerdasanBuatan. Abstract Artificial Intelligence (AI) techniques are successfully used and applied in a wide range of areas, includingmanufacturing, engineering, economics, medicine and military. In recent years, there has been anincreasing interest in Game Artificial Intelligence or Game AI. Game AI refers to techniques applied incomputer and video games such as learning, pathfinding, planning, and many others for creating intelligentand autonomous behaviour to the characters in games. The main objective of this paper is to highlightseveral most common of the AI techniques for designing and controlling the computer-based charactersto play Ms. Pac-Man game between years 2005-2012. The Ms. Pac-Man is one of the games that used asbenchmark for comparison of autonomous controllers in a series of international Game AI competitions.An extensive content analysis method was conducted through critical review on previous literature relatedto the field. Findings highlight, although there was various and unique techniques available, the majorlimitation of previous studies for creating the Ms. Pac-Man game characters is a lack of generalizationcapability across different game characters. The findings could provide the future direction for researchersto improve the Generalization A.I capability of game characters in the Game Artificial Intelligence market.

Determining the factors affecting the technical efficiency scores of public hospitals using different regression methods

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Bayram Şahin ◽  
Gülnur İlgün ◽  
Seda Sönmez
Keyword(s):  
Public Hospitals ◽  
Regression Analyses ◽  
Tobit Regression ◽  
Control Variables ◽  
Content Type ◽  
Factors Affecting ◽  
Provincial Level ◽  
Regression Methods ◽  
Input And Output ◽  
Dea Method

PurposeThis study aims to identify the efficiency scores of hospitals affiliated to the Ministry of Health in Turkey between the years of 2010–2015 at provincial level and to reveal the factors that affect the efficiency scores.Design/methodology/approachThe two-stage data envelopment analysis (DEA) method was used to achieve the study purpose. In the first stage, DEA method based on input-oriented Charnes–Cooper–Rhodes (CCR) model was performed to calculate the efficiency scores of public hospitals at the provincial level between 2010 and 2015, and in the second stage, Tobit regression and linear regression analyses were used to identify whether the efficiency scores of provinces are affected by the input, output and control variables.FindingsUpon the analysis, the average efficiency scores of 81 provinces by years were found to vary between 0.79 and 0.89. According to both regression analyses, all of the input and output variables were found to have significant effects on the efficiency scores of provinces while only the population of province among the control variables was identified as the factor with an effect on the efficiency scores of provinces (p < 0.05).Practical implicationsThe results of this study are thought to guide health policymakers and managers in terms of both determining efficient and inefficient hospitals at the provincial level and revealing which variables should be taken into account in order to increase efficiency.Originality/valueThe study differs from previous studies on the efficiency of hospitals. First, although previous studies were generally descriptive studies to determine the efficiency level of hospitals, this study is an analytical study that tries also to show the factors affecting the efficiency of hospitals. In addition, while examining the effect of input and output variables on efficiency scores, control variables were also included in the study.

Sign in / Sign up

Export Citation Format

Share Document