Light responsive curve selection for photosynthesis operator of APOA
International Journal of Bio-Inspired Computation
Time-varying social emotional optimisation algorithm
International Journal of Computing Science and Mathematics
APOA with parabola model for directing orbits of chaotic systems
International Journal of Bio-Inspired Computation
Artificial plant optimisation algorithm with three-period photosynthesis
International Journal of Bio-Inspired Computation
Reactive power optimisation of power system with APPM
International Journal of Computing Science and Mathematics
Fuzzy PID control of induction motor speed regulating system based on PLC
International Journal of Wireless and Mobile Computing
Automatic semantic annotation by using fuzzy theory for natural images
International Journal of Wireless and Mobile Computing
Hybrid ABC/PSO to solve travelling salesman problem
International Journal of Computing Science and Mathematics
Heating exchange process PIDNN control system research based on T-S fuzzy model
International Journal of Wireless and Mobile Computing
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In order to train Artificial Neural Networks (ANNs), we used a new stochastic optimisation algorithm that simulates the plant growing process. It designs an artificial photosynthesis operator and an artificial phototropism operator to mimic photosynthesis and phototropism mechanisms, we call it briefly APPM algorithm. In this algorithm, each individual is called a branch, and the sampled points are regarded as the branch growing trajectory. Phototropism operator is designed to introduce the fitness function value, and it is also used to decide the growing direction. In this paper, we apply APPM algorithm to train the connection weights for ANN. To assess the performance of our APPM-trained ANN (APPMANN), two real-world problems, named Cleveland heart disease classification problem and sunspot number forecasting problem, are adopted. Simulation results show that APPMANN increases the performance significantly when compared with other sophisticated machine learning techniques proposed in recent years.