Application of Adaptive Neuro-Fuzzy Inference System-Non-dominated Sorting Genetic Algorithm-II (ANFIS-NSGAII) for Modeling and Optimizing Somatic Embryogenesis of Chrysanthemum
نویسندگان
چکیده
منابع مشابه
Modeling of Weld Bead Geometry Using Adaptive Neuro-Fuzzy Inference System (ANFIS) in Additive Manufacturing
Additive Manufacturing describes the technologies that can produce a physical model out of a computer model with a layer-by-layer production process. Additive Manufacturing technologies, as compared to traditional manufacturing methods, have the high capability of manufacturing the complex components using minimum energy and minimum consumption. These technologies have brought about the possibi...
متن کاملBreast Cancer Risk Assessment Using adaptive neuro-fuzzy inference system (ANFIS) and Subtractive Clustering Algorithm
Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used. First,...
متن کاملImplementation of Adaptive Neuro-Fuzzy Inference System (Anfis) for Performance Prediction of Fuel Cell Parameters
Fuel cells are potential candidates for storing energy in many applications; however, their implementation is limited due to poor efficiency and high initial and operating costs. The purpose of this research is to find the most influential fuel cell parameters by applying the adaptive neuro-fuzzy inference system (ANFIS). The ANFIS method is implemented to select highly influential parame...
متن کاملBreast Cancer Risk Assessment Using adaptive neuro-fuzzy inference system (ANFIS) and Subtractive Clustering Algorithm
Introduction: The adaptive neuro-fuzzy inference system (ANFIS) is a soft computing model based on neural network precision and fuzzy decision-making advantages, which can highly facilitate diagnostic modeling. In this study we used this model in breast cancer detection. Methodology: A set of 1,508 records on cancerous and non-cancerous participant’s risk factors was used. First,...
متن کاملOptimal Distribution System Reconfiguration Using Non-dominated Sorting Genetic Algorithm (NSGA-II)
In this paper, a Non-dominated Sorting Genetic Algorithm-II (NSGA-II) based approach is presented for distribution system reconfiguration. In contrast to the conventional GA based methods, the proposed approach does not require weighting factors for conversion of multi-objective function into an equivalent single objective function. In order to illustrate the performance of the proposed method,...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Frontiers in Plant Science
سال: 2019
ISSN: 1664-462X
DOI: 10.3389/fpls.2019.00869