A measurement-based methodology for the determination of validity domains of prediction models in urban environment

2000 ◽  
Vol 49 (5) ◽  
pp. 1508-1515 ◽  
Author(s):  
M. Barbiroli ◽  
C. Carciofi ◽  
G. Falciasecca ◽  
M. Frullone ◽  
P. Grazioso
Keyword(s):  
Urban Environment ◽  
Prediction Models

scholarly journals Formation and maintenance of the territorial balance in the conditions of high-rise construction in the city

2018 ◽  
Vol 33 ◽  
pp. 01034
Author(s):  
Tatiana Kisel
Keyword(s):  
Urban Development ◽  
Urban Environment ◽  
Social Infrastructure ◽  
City Development ◽  
High Rise ◽  
The City

High-rise construction results in the need of planning of infrastructure facilities, taking into account the increase in loading, as high-rise construction allows to place considerably bigger number of residents in the limited territory. For this purpose it is necessary to estimate the required and actual level of providing the population with each particular type of the facilities of social infrastructure. The compliance of required and actual level of providing can be characterized as the territorial balance, while the discrepancy acts as the territorial imbalance. The article is devoted to the development of such instruments of planning of urban development, which will allow to create the qualitative urban environment, founded on the territorial balances. Namely, it is devoted to the calculation of level of providing the population with the facilities of social infrastructure, to the determination of level of the imbalance in absolute and relative units and also to the ranging of imbalances on urgency of their elimination. The size of the imbalance is of great importance for planning and realization of managerial influences from the executive authorities, operating the city development. In order to determine the urgency of realization of actions for the construction of facilities of social infrastructure it is offered to range the imbalances according to their size, having determined the deviation size from balance, which is so insignificant that it does not demand any managerial influences (it can be characterized as balance) and also the groups of the imbalances, differing in urgency of managerial influences, directed to the decrease and elimination of the revealed imbalance.

Modeling of Gear Hobbing: Part II — A Computer Supported Experimental-Analytical Determination of the Wear Progress to Optimize the Tool Life Time

1999 ◽  
Author(s):  
Konstantinos D. Bouzakis ◽  
Spiros Kombogiannis ◽  
Aristomenis Antoniadis ◽  
Nectarios Vidakis
Keyword(s):  
Tool Wear ◽  
Prediction Models ◽  
Digital Simulation ◽  
Life Time ◽  
Analytical Determination ◽  
Tool Wear Prediction ◽  
Gear Hobbing ◽  
User Friendly ◽  
Continuous Enrichment

Abstract Tool wear prediction models for gear hobbing were presented in the first part of this paper. To determine the constants of the equations used in these models, fly hobbing experiments with uncoated and coated HSS tools were conducted. Hereby, it was necessary to modify the fly hobbing kinematics from continuous tangential feed to continuous axial feed. The experimental data were evaluated, and correlated to the analytical ones, elaborated through the described digital simulation of the cutting process. The determined constants of the wear laws for the investigated tools were used in a further developed user friendly software, enabling the prediction of the tool wear accomplishment in gear hobbing. On that account the wear development can be precisely foreseen and the tangential shift of the tool is optimized. The open and modular structure of the developed code enables the continuous enrichment of its database with other type of coating and workpiece materials. With the aid of the aforementioned techniques, the superiority of coated HSS tools in comparison to uncoated ones is also quantitatively exhibited.

Operational Evaluation of a Selective Consensus in the Western North Pacific Basin

2007 ◽  
Vol 22 (3) ◽  
pp. 671-675 ◽  
Author(s):  
Charles R. Sampson ◽  
John A. Knaff ◽  
Edward M. Fukada
Keyword(s):  
North Pacific ◽  
Western North Pacific ◽  
Systematic Approach ◽  
Prediction Models ◽  
Weather Prediction ◽  
Pacific Basin ◽  
Joint Typhoon Warning Center ◽  
Numerical Weather Prediction Models ◽  
North Pacific Basin

Abstract The Systematic Approach Forecast Aid (SAFA) has been in use at the Joint Typhoon Warning Center since the 2000 western North Pacific season. SAFA is a system designed for determination of erroneous 72-h track forecasts through identification of predefined error mechanisms associated with numerical weather prediction models. A metric for the process is a selective consensus in which model guidance suspected to have 72-h error greater than 300 n mi (1 n mi = 1.85 km) is first eliminated prior to calculating the average of the remaining model tracks. The resultant selective consensus should then provide improved forecasts over the nonselective consensus. In the 5 yr since its introduction into JTWC operations, forecasters have been unable to produce a selective consensus that provides consistent improved guidance over the nonselective consensus. Also, the rate at which forecasters exercised the selective consensus option dropped from approximately 45% of all forecasts in 2000 to 3% in 2004.

scholarly journals Model Analisis Prediksi Kebangkrutan Bank Swasta Nasional Periode 2002-2006

2012 ◽  
Vol 3 (2) ◽  
pp. 719
Author(s):  
Agha Swara Ganesha ◽  
Tomy G. Soemapradja ◽  
Darman Darman ◽  
Desmizar Desmizar
Keyword(s):  
Commercial Bank ◽  
Good Accuracy ◽  
Prediction Models ◽  
Multiple Discriminant Analysis ◽  
Average Accuracy ◽  
Private Banks ◽  
Model Determination ◽  
Z Value ◽  
Value Model

There are two main objectives to be achieved by this study:to determine the accuracy level of prediction models of health national private banks using CAMEL ratios, and model the value of Z for the national private commercial banks by using multiple discriminant analysis (MDA) as well as Altman Z values on the model. Determination of the model using the Z value ratios banking health of Capital, Assets, Earnings and Liability (CAEL), then create a new Z value model specifically for national private commercial bank in Indonesia by using statistical analysis of MDA, with SPSS. The samples used were 30 banks, consisting of 19 survived banks in 2002 and 11 bankrupt banks in the same year. The results showed that the model value of Z in the year 2003-2006 cannot reach good accuracy when measured on a per year. Instead, the new Z value model generated by this study has better accuracy in predicting the rate of bankruptcy cases nationwide private commercial bank in Indonesia (86.7%) in 2002 and an average accuracy of 71.67% for the 4-year period of the review.

scholarly journals Identification of Copper in Stems and Roots of Jatropha curcas L. by Hyperspectral Imaging

Processes ◽  
2020 ◽  
Vol 8 (7) ◽  
pp. 823
Author(s):  
Juan Francisco García-Martín ◽  
Amanda Teixeira Badaró ◽  
Douglas Fernandes Barbin ◽  
Paloma Álvarez-Mateos
Keyword(s):  
Jatropha Curcas ◽  
Near Infrared ◽  
Prediction Models ◽  
Plant Stress ◽  
Principal Component ◽  
Linear Discriminant ◽  
Jatropha Curcas L ◽  
Potential Applications

The in situ determination of metals in plants used for phytoremediation is still a challenge that must be overcome to control the plant stress over time due to metals uptake as well as to quantify the concentration of these metals in the biomass for further potential applications. In this exploratory study, we acquired hyperspectral images in the visible/near infrared regions of dried and ground stems and roots of Jatropha curcas L. to which different amounts of copper (Cu) were added. The spectral information was extracted from the images to build classification models based on the concentration of Cu. Optimum wavelengths were selected from the peaks and valleys showed in the loadings plots resulting from principal component analysis, thus reducing the number of spectral variables. Linear discriminant analysis was subsequently performed using these optimum wavelengths. It was possible to differentiate samples without addition of copper from samples with low (0.5–1% wt.) and high (5% wt.) amounts of copper (83.93% accuracy, >0.70 sensitivity and specificity). This technique could be used after enhancing prediction models with a higher amount of samples and after determining the potential interference of other compounds present in plants.

Determination of Flood Risk Considering Flood Control Ability and Urban Environment Risk

2015 ◽  
Vol 48 (9) ◽  
pp. 757-768
Author(s):  
Eui Hoon Lee ◽  
◽  
Hyeon Seok Choi ◽  
Joong Hoon Kim
Keyword(s):  
Urban Environment ◽  
Flood Risk ◽  
Flood Control

Determination of Algorithms Making Balance Between Accuracy and Comprehensibility in Churn Prediction Setting

2011 ◽  
Vol 1 (2) ◽  
pp. 39-54 ◽  
Author(s):  
Hossein Abbasimehr ◽  
Mohammad Jafar Tarokh ◽  
Mostafa Setak
Keyword(s):  
Logistic Regression ◽  
Predictive Modeling ◽  
Prediction Models ◽  
Rule Induction ◽  
Parameter Setting ◽  
Churn Prediction ◽  
Training Set ◽  
Rule Based ◽  
The Past

Predictive modeling is a useful tool for identifying customers who are at risk of churn. An appropriate churn prediction model should be both accurate and comprehensible. However, reviewing the past researches in this context shows that much attention is paid to accuracy of churn prediction models than comprehensibility of them. This paper compares three different rule induction techniques from three categories of rule based classifiers in churn prediction context. Furthermore logistic regression (LR) and additive logistic regression (ALR) are used. After parameter setting, eight distinctive algorithms, namely C4.5, C4.5 CP, RIPPER, RIPPER CP, PART, PART CP, LR, and ALR, are obtained. These algorithms are applied on an original training set with the churn rate of 30% and another training set with the churn rate of 50%. Only the models built by applying these algorithms on a training set with the churn rate of 30% make balance between accuracy and comprehensibility. In addition, the results of this paper show that ALR can be an excellent alternative for LR, when models only from accuracy perspective are evaluated.

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