This paper studies the fault diagnosis method of pneumatic control valve. Firstly, the faults
characteristics of pneumatic control valves are analyzed according to the operating principle …

Traffic flow anomaly detection is helpful to improve the efficiency and reliability of detecting
fault behavior and the overall effectiveness of the traffic operation. The data detected by the …

Accurate and real-time short-term traffic flow forecasting is an important prerequisite for
traffic guidance and control. A single forecasting method is difficult to handle all the …

Redundant nodes in a kernel incremental extreme learning machine (KI-ELM) increase
ineffective iterations and reduce learning efficiency. To address this problem, this study …

Traffic flow prediction is an essential foundation of intelligent traffic management, and its
accuracy and timeliness are essential indicators for effective traffic diversion and alleviation …

This paper explicates hybrid optimization driven Extreme Machine Learning (ELM) strategy
is developed with feed forward neural network (FFNN) for the classification of data and …

In the bio-molecular field, epitope classification is essential in vaccine development. A
machine learning-based approach has been used for epitope classification using peptide …

The progression of organizing and classifying data components based on pre‐established
criteria is known as data classification. In data classification problems, machine learning …

Internet of Things (IoT) is the core concept for smart cities. The foremost functionality of IoT is
to access the data collected from the shared devices over the communication technologies …

Traffic flow prediction is an effective strategy to assess traffic conditions and alleviate traffic
congestion. Influenced by external non-stationary factors and road network structure, traffic …