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ANFIS Modeling Based on Full Factorial Design

2006 IEEE International Conference on Industrial Technology, 2006
Adaptive network based fuzzy inference system (ANFIS) is an intelligent neuro-fuzzy technique used for modeling and control of ill-defined and uncertain systems. ANFIS is based on the input-output data pairs of the system under consideration. The size of the input-output data set is very crucial when the data available is very less and the generation ...
Mrinal Buragohain, Chitralekha Mahanta
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Full Factorial Designs and Distracted Fractions

1998
Design of Experiments is a branch of Statistics, which has a long tradition in the use of algebraic methods. In general all this methods where developed in the case of binary experiments, with level coding either 0, 1 and -1, 1 and refer to computations in Z_2 The classical theory fully exploits the characteristics of the binary case, in particular the
ROBBIANO, LORENZO, ROGANTIN, MARIA PIERA
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Full Factorial Design Based ANFIS Model for Complex Systems

2006 Annual IEEE India Conference, 2006
In this paper we propose an Adaptive Network based Fuzzy Inference system (ANFIS) model where the number of data pairs employed for training is minimized by application of an engineering statistical technique called full factorial design. Our proposed method is experimentally validated by applying it to the benchmark Box and Jenkins gas furnace data ...
M. Buragohain, C. Mahanta
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Randomised controlled trials with full factorial designs

BMJ, 2012
Researchers explored the effectiveness of three interventions in preventing falls among older people. The three interventions were group based exercise, home hazard management, and vision improvement. A randomised controlled trial with a full factorial design was used. The control treatment was no intervention.
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Full Factorial Design: Optimization for Nanogel Formation

Journal of Research in Nanoscience and Nanotechnology
The Design of Experiments, DoE, is a set of applied statistics tools for systematically classifying and quantifying cause and effect relationships between variables and outputs in the studied process, which may lead to the discovery of the settings and conditions under which the process becomes optimized.
Nur Fathin Amirah Shafie   +4 more
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Full factorial design for optimization of magnesium alkalinization additive

Transportation Geotechnics, 2019
Abstract Intensive research using chemical stabilization for improving subgrade soil has become increasingly popular around the globe. The alkaline activator additive provides an improved and effective alternative for cement, and also produces comparatively less CO2 emissions. This paper studied the factors that contribute to the strength development
Nurmunira Muhammad, Sumi Siddiqua
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HOMOGENIZATION METHODS FOR MULTISCALE PROCESS MODELING THROUGH FULL FACTORIAL DESIGN

American Society for Composites 2023, 2023
Crucial to developing the next generation of high-performance composites are multiscale process models which have the capacity to predict in-service performance affecting residual stresses and deformations generated during manufacturing. Length scale and geometrical complexity of composites increase in tandem; thus, process models must rely upon ...
MICHAEL N. OLAYA, MARIANNA MAIARĂ™
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A Full-Factorial Design Approach for Coordinate Transformation

Arabian Journal for Science and Engineering, 2013
The aim of this study is to analyze the role of experimental factors in the affine coordinate transformation of cadastral maps using a 23 factorial design. The selected experimental factors and their respective levels include a map scale of 1/500–1/1,000, a number of common points 4 and 20, and the least square and least absolute value adjustment ...
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More Full Factorial Design Examples

2009
This chapter contains the analysis of three interesting experiments reported in the literature.
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