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Chaotic gaining sharing knowledge-based optimization algorithm: an improved metaheuristic algorithm for feature selection

The gaining sharing knowledge based optimization algorithm (GSK) is recently developed metaheuristic algorithm, which is based on how humans acquire and share knowledge during their life-time. This paper investigates a modified version of the GSK algorithm to find the best feature subsets. Firstly, it represents a binary variant of GSK algorithm by employing a probability estimation operator (Bi-GSK) on the two main pillars of GSK algorithm. And then, the chaotic maps are used to enhance the performance of the proposed algorithm. Ten different types of chaotic maps are considered to adapt the
Artificial Intelligence
Circuit Theory and Applications
Software and Communications

Chaotic system modelling using a neural network with optimized structure

In this work, the Artificial Neural Networks (ANN) are used to model a chaotic system. A method based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to determine the best parameters of a Multilayer Perceptron (MLP) artificial neural network. Using NSGA-II, the optimal connection weights between the input layer and the hidden layer are obtained. Using NSGA-II, the connection weights between the hidden layer and the output layer are also obtained. This ensures the necessary learning to the neural network. The optimized functions by NSGA-II are the number of neurons in the

Artificial Intelligence
Circuit Theory and Applications

Chaotic system modelling using a neural network with optimized structure

In this work, the Artificial Neural Networks (ANN) are used to model a chaotic system. A method based on the Non-dominated Sorting Genetic Algorithm II (NSGA-II) is used to determine the best parameters of a Multilayer Perceptron (MLP) artificial neural network. Using NSGA-II, the optimal connection weights between the input layer and the hidden layer are obtained. Using NSGA-II, the connection weights between the hidden layer and the output layer are also obtained. This ensures the necessary learning to the neural network. The optimized functions by NSGA-II are the number of neurons in the

Artificial Intelligence
Circuit Theory and Applications

AROMA: Automatic generation of radio maps for localization systems

Current methods for building radio maps for wireless localization systems require a tedious, manual and error-prone calibration of the area of interest. Each time the layout of the environment is changed or different hardware is used, the whole process of location fingerprinting and constructing the radio map has to be repeated. The process gets more complicated in the case of localizing multiple entities in a device-free scenario, since the radio map needs to take all possible combinations of the location of the entities into account. In this demo, we present a novel system (AROMA) that is

Artificial Intelligence
Circuit Theory and Applications
Software and Communications

Transmission power adaptation for cognitive radios

In cognitive radio (CR) networks, determining the optimal transmission power for the secondary users (SU) is crucial to achieving the goal of maximizing the secondary throughput while protecting the primary users (PU) from service disruption and interference. In this paper, we propose an adaptive transmission power scheme for cognitive terminals opportunistically accessing a primary channel. The PU operates over the channel in an unslotted manner switching activity at random times. The secondary transmitter (STx) adapts its transmission power according to its belief regarding the PU's state of

Artificial Intelligence
Circuit Theory and Applications
Software and Communications

FPGA-Based Memristor Emulator Circuit for Binary Convolutional Neural Networks

Binary convolutional neural networks (BCNN) have been proposed in the literature for resource-constrained IoTs nodes and mobile computing devices. Such computing platforms have strict constraints on the power budget, system performance, processing and memory capabilities. Nonetheless, the platforms are still required to efficiently perform classification and matching tasks needed in various applications. The memristor device has shown promising results when utilized for in-memory computing architectures, due to its ability to perform storage and computation using the same physical element

Artificial Intelligence
Circuit Theory and Applications
Software and Communications

Fractional Order Sliding Mode PID Controller/Observer for Continuous Nonlinear Switched Systems with PSO Parameter Tuning

In this article a fractional order sliding mode PID controller and observer for the stabilization of continuous nonlinear switched systems is proposed. The design of the controller and observer is done following the separation principle, this means that the observer and controller are designed in a separate fashion, so a hybrid controller is implemented by designing the sliding mode controller part using an integral sliding mode surface along with a PIλDμ controller part which is the fractional order PID controller that is implemented to stabilizes the system. For the observer part, an

Artificial Intelligence
Circuit Theory and Applications
Software and Communications

Two-Degree of Freedom Proportional Integral Derivative (2-DOF PID) Controller for Robotic Infusion Stand

Infusion Stand is one of the medical supportive tools in the field of biomedical that assist in holding and carrying medications to patients via intravenous injections. Mobilization of Infusion Stand from a place to another place is necessary not only for the patients itself but also for the nurses. Therefore, this leads to not only uneasiness but also inconvenience for both parties. Therefore, to improve the existing situation and current Infusion Stand in the market, a proposal to design and implement a prototypic Robotic Infusion Stand is submitted. In this paper, 2-Degree of Freedom

Artificial Intelligence
Circuit Theory and Applications
Software and Communications

Gray Wolf Optimization of Fractional Order Control of 3-Omni Wheels Mobile Robot: Experimental Study

Committing robotics with artificial intelligence becomes mandatory collaboration with distinct environments. Omnidirectional Wheeled (Omni-WD) mobile robots are one of the robots that interact with humans in various circumstances, where it is important to function effectively and accurately. In this paper, the distinction of a 3WD-Omni model and control using machine vision is demonstrated. The use of fractional order (FO) calculus has been stated to increase the degrees of freedom of the controller over the integer ones. Hybridization of FO control and metaheuristics optimization is reported

Artificial Intelligence
Circuit Theory and Applications
Mechanical Design

Fractional Order Two Degree of Freedom PID Controller for a Robotic Manipulator with a Fuzzy Type-2 Compensator

In this paper a novel strategy for the position control and trajectory tracking of robotic manipulators is proposed. This strategy consists of an independent two degree of freedom PID controller for a two links robotic arm. Due to the capability of two degree of freedom PID controllers to deal with disturbances, each link is controlled independently considering that the disturbance does not affect the system performance due to the robustness of the closed loop system. Then, a fuzzy type-2 centralized compensator is implemented to drive the orientation variables with the desired trajectory in

Artificial Intelligence
Circuit Theory and Applications
Mechanical Design