Local Positioning System Based on Artificial Neural Networks
نویسندگان
چکیده
This work describes a complete indoor location system, from its creation, development and deployment. This location system is a capable way of retrieving the position of wireless devices using a simple software solution, no additional hardware is necessary. The positioning engine uses artificial neural networks (ANN) to describe the behaviour of a specific indoor propagation channel. The training of the ANN is assured using a slight variation of the radio frequency fingerprinting technique. Results show that the location system has high accuracy with an average error below two meters.
منابع مشابه
Solving the local positioning problem using a four-layer artificial neural network
Today, the global positioning systems (GPS) do not work well in buildings and in dense urban areas when there is no lines of sight between the user and their satellites. Hence, the local positioning system (LPS) has been considerably used in recent years. The main purpose of this research is to provide a four-layer artificial neural network based on nonlinear system solver (NLANN) for local pos...
متن کاملYarn tenacity modeling using artificial neural networks and development of a decision support system based on genetic algorithms
Yarn tenacity is one of the most important properties in yarn production. This paper addresses modeling of yarn tenacity as well as optimally determining the amounts of the effective inputs to produce yarn with desired tenacity. The artificial neural network is used as a suitable structure for tenacity modeling of cotton yarn with 30 Ne. As the first step for modeling, the empirical data is col...
متن کاملOn the convergence speed of artificial neural networks in the solving of linear systems
Artificial neural networks have the advantages such as learning, adaptation, fault-tolerance, parallelism and generalization. This paper is a scrutiny on the application of diverse learning methods in speed of convergence in neural networks. For this aim, first we introduce a perceptron method based on artificial neural networks which has been applied for solving a non-singula...
متن کاملSeven-Level Direct Torque Control of Induction Motor Based on Artificial Neural Networks with Regulation Speed Using Fuzzy PI Controller
In this paper, the author proposes a sensorless direct torque control (DTC) of an induction motor (IM) fed by seven-level NPC inverter using artificial neural networks (ANN) and fuzzy logic controller. Fuzzy PI controller is used for controlling the rotor speed and ANN applied in switching select stator voltage. The control method proposed in this paper can reduce the torque, stator flux and to...
متن کاملDiagnosis Prediction of Lichen Planus, Leukoplakia and Oral Squamous Cell Carcinoma by using an Intelligent System Based on Artificial Neural Networks
Introduction: Diagnosis, prediction and control of oral lesions is usually done classically based on clinical signs and histopathologic features. Due to lack of timely diagnosis in all conventional methods or differential diagnosis, biopsy of patient is needed. Therefore, the patient might be irritated. So, an intelligent method for quick and accurate diagnosis would be crucial. Intelligent sys...
متن کامل