Artificial Intelligence in Construction Management : Evolutionary Fuzzy Hybrid Neural Network as decision-making machine

116.68 SGD
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105.02

Product Description

Many studies have found that High-order neuralnetwork (HONN) is enables to boost neural networkperformance. This research utilize a hybrid modelwith HONN and Linear Neural Network (NN) concepts todevelop high-order and linear neural connectors forlayer connections. Consequently, this developed HNNwill involve a linear/nonlinear switch for eachneural layer connection. Furthermore, fuzzy logic(FL) has already been introduced to neural networkand it is also found that the combination of FL andFNN has been proof-reading. Furthermore, fuzzy logic(FL) also has been introduced to neural network andbeen proofed with fuzzy neural network (FNN).Therefore, this research fuses fuzzy logicadditionally to develop a fuzzy hybrid neuralnetwork (FHNN) architecture. Sequentially, geneticalgorithm (GA) is employed to globally optimizemembership function of FL and HNN topology andparameters.

§16§Many studies have found that High-order neural §network (HONN) is enables to boost neural network §performance. This research utilize a hybrid model §with HONN and Linear Neural Network (NN) concepts to §develop high-order and linear neural connectors for §layer connections. Consequently, this developed HNN §will involve a linear/nonlinear switch for each §neural layer connection. Furthermore, fuzzy logic §(FL) has already been introduced to neural network §and it is also found that the combination of FL and §FNN has been proof-reading. Furthermore, fuzzy logic §(FL) also has been introduced to neural network and §been proofed with fuzzy neural network (FNN). §Therefore, this research fuses fuzzy logic §additionally to develop a fuzzy hybrid neural §network (FHNN) architecture. Sequentially, genetic §algorithm (GA) is employed to globally optimize §membership function of FL and HNN topology and §parameters.

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