Pattern Analysis and Intelligent Systems
Ali Ahmad Ali
Volume 6, Issue 2 , May 2020, , Pages 71-78
Abstract
Abstract— An educational platform is presented here for the beginner students in the Simulation and Artificial Intelligence sciences. It provides with a start point of building and simulation of the manipulators, especially of 2R planar Robot. It also displays a method to replace the inverse kinematic ...
Read More
Abstract— An educational platform is presented here for the beginner students in the Simulation and Artificial Intelligence sciences. It provides with a start point of building and simulation of the manipulators, especially of 2R planar Robot. It also displays a method to replace the inverse kinematic model (IKM) of the Robot with a simpler one, by using a Multi-Layer Perceptron Neural Network (MLP-NN), to make the end-effector able to track a specific path, which has a rectangular shape (in this article), and allocated in the robot's workspace. The method is based on Back-Propagation Levenberg Marquardt algorithm. This paper also suggests a good strategy for the simulation of the robot's motion in Matlab to tell the beginners how the operation could be done quite closely to the built-in Matlab functions. The control part was ignored here for the simplicity. So we can classify this paper as a manual in the robotic world.
Pattern Analysis and Intelligent Systems
asma naeimi; minoo soltanshahi; amir rajabi
Volume 3, Issue 1 , February 2017, , Pages 19-30
Abstract
One of the most common and most dangerous diseases of blood fats are such as heart disease, diabetes and stroke, heart and brain. It can control the timely diagnosis, treatment and then prevention of complications is become very effective even without using medicine. Heart disease and diabetes file if ...
Read More
One of the most common and most dangerous diseases of blood fats are such as heart disease, diabetes and stroke, heart and brain. It can control the timely diagnosis, treatment and then prevention of complications is become very effective even without using medicine. Heart disease and diabetes file if patients has useful information that can be used to estimate blood fat timely diagnosis. In this paper we introduce a method based on data mining according to the information of patients' medical records to predict and detect blood lipid cardiovascular. And to identify patients with high blood lipids,we use a category based on neural network without feedback and pso algorithm to train the neural network to determine the appropriate value to reduce error the weights of the neural network . Simulation is done in MATLAB environment by using Body Fat data set, it shows the accuracy of 93.22 percent compared to the same methods, which means high accurate, higher detection sensitivity and Democrats.