A novel particle swarm optimization algorithm with Levy flight
Particle swarm optimization (PSO) is one of the well-known population-based techniques
used in global optimization and many engineering problems. Despite its simplicity and …
used in global optimization and many engineering problems. Despite its simplicity and …
Constructing infinitely many attractors in a programmable chaotic circuit
In this paper, we modify the Sprott M chaotic system to provide infinitely many co-existing
attractors by replacing the offset boosting parameter with a periodic function giving what we …
attractors by replacing the offset boosting parameter with a periodic function giving what we …
Hardware design and implementation of a novel ANN-based chaotic generator in FPGA
This paper presents a novel hardware implementation of Artificial Neural Networks (ANNs)
for modeling of the Pehlivan–Uyaroglu Chaotic System (PUCS) on Field Programmable …
for modeling of the Pehlivan–Uyaroglu Chaotic System (PUCS) on Field Programmable …
Artificial Neural Networks based thermodynamic and economic analysis of a hydrogen production system assisted by geothermal energy on Field Programmable Gate …
In this study, the thermodynamic and economic analysis of a geothermal energy assisted
hydrogen production system was performed using real-time Artificial Neural Networks on …
hydrogen production system was performed using real-time Artificial Neural Networks on …
New mixed-coding PSO algorithm for a self-adaptive and automatic learning of Mamdani fuzzy rules
Thanks to its algorithmic performances, PSO algorithm becomes a popular tune tool for fuzzy
systems in literature. However, it still encounters many complications, especially when …
systems in literature. However, it still encounters many complications, especially when …
A robust hybrid approach based on particle swarm optimization and genetic algorithm to minimize the total machine load on unrelated parallel machines
MSS Mir, J Rezaeian - Applied Soft Computing, 2016 - Elsevier
This paper dealt with an unrelated parallel machines scheduling problem with past-
sequence-dependent setup times, release dates, deteriorating jobs and learning effects, in …
sequence-dependent setup times, release dates, deteriorating jobs and learning effects, in …
Hardware implementation of neural network with Sigmoidal activation functions using CORDIC
V Tiwari, N Khare - Microprocessors and Microsystems, 2015 - Elsevier
Activation function is the most important function in neural network processing. In this article,
the field-programmable gate array (FPGA)-based hardware implementation of a multilayer …
the field-programmable gate array (FPGA)-based hardware implementation of a multilayer …
Prediction of surface roughness and cutting zone temperature in dry turning processes of AISI304 stainless steel using ANFIS with PSO learning
This paper presents an approach for modeling and prediction of both surface roughness and
cutting zone temperature in turning of AISI304 austenitic stainless steel using multi-layer …
cutting zone temperature in turning of AISI304 austenitic stainless steel using multi-layer …
Flow-based anomaly detection in high-speed links using modified GSA-optimized neural network
M Sheikhan, Z Jadidi - Neural Computing and Applications, 2014 - Springer
Ever growing Internet causes the availability of information. However, it also provides a
suitable space for malicious activities, so security is crucial in this virtual environment. The …
suitable space for malicious activities, so security is crucial in this virtual environment. The …
An optimal adaptive robust PID controller subject to fuzzy rules and sliding modes for MIMO uncertain chaotic systems
MJ Mahmoodabadi, RA Maafi, M Taherkhorsandi - Applied Soft Computing, 2017 - Elsevier
In this paper, an optimal adaptive robust PID controller based on fuzzy rules and sliding
modes is introduced to present a general scheme to control MIMO uncertain chaotic …
modes is introduced to present a general scheme to control MIMO uncertain chaotic …