In the paper, a new method of tool wear detection with cutting conditions and detected signals is presented, which includes the model of wavelet fuzzy neural network with acoustic emission (AE) and the model of fuzzy classification with motor current. The results of tool wear estimated by cutting conditions and detected signals (spindle motor current, feed motor current and AE) are fused by fuz...

This dissertation presents a novel approach to combining wavelet networks and multilayer feedforward network for fuzzy logic control systems. Most of the existing methods focus on implementing the Takagi-Sugano fuzzy reasoning model and have demonstrated its effectiveness. However, these methods fail to keep the knowledge structure, which is critical in interpreting the learning process and pro...

Accurate and computationally efficient means of electrocardiography (ECG) arrhythmia detection has been the subject of considerable research efforts in recent years. Intelligent computing tools such as artificial neural network (ANN) and fuzzy logic approaches are demonstrated to be competent when applied individually to a variety of problems. Recently, there has been a growing interest in comb...

Aimed at overcoming subjectivity and improving the accuracy of traditional production performance evaluation methods for manufacturing enterprises, a new model of performance evaluation was proposed based on rough sets and a wavelet neural network (RS WNN). Firstly, an evaluation index system considering innovation performance was constructed. Secondly, a theory of rough sets and fuzzy mathemat...

In this paper, an intelligent swarm based-wavelet neural network for affective mobile designed is presented. The contribution on this paper is to develop a new intelligent particle swarm optimization (iPSO), where a fuzzy logic system developed based on human knowledge is proposed to determine the inertia weight for the swarm movement of PSO and the control parameter of a newly introduced cross...

Winding hotspot temperature is the key factor affecting the load capacity and service life of transformers. For the early detection of transformer winding hotspot temperature anomalies, a new prediction model for the hotspot temperature fluctuation range based on fuzzy information granulation (FIG) and the chaotic particle swarm optimized wavelet neural network (CPSO-WNN) is proposed in this pa...