Studi Penerapan ANN (Artificial Neural Network) untuk Menghilangkan Harmonisa pada Gedung Pusat Komputer

In electrical systems, power quality is something that must be considered, the power quality assessment can be viewed from various aspects, such as the continuity in the supply of electric energy, stable frequency and voltage on the transmission of electrical energy, and power factor. Non-linear load is a contributor of harmonics that can interfere with the quality of electrical power so used filters for the prevention of electrical harmonics. As science, it is increasingly developing technologies to minimize electrical harmonics, one of which is the Artificial Neural Network. This research will discuss the characteristics of the artificial neural network is used to solve the problem of harmonics on PUSKOM building

Simulation studies relating to rudder roll stabilization of a container ship using neural networks

RRS (Rudder Roll Stabilization) of Ships is a difficult problem because of its associated non-linear dynamics, coupling effects and complex control requirements. This paper proposes a solution of this stabilization problem that is based on an ANN (Artificial Neural Network) controller. The controller has been trained using supervised learning. The simulation studies have been carried out using MATLAB and a non-linear model of a container ship. It has been demonstrated that the proposed controller regulates heading and also controls roll angle very successfully

Development and training of an Artificial Neural Network in Unity3D, including a game to interact with it and observe its performance

Treball final de Grau en Disseny i Desenvolupament de Videojocs. Codi: VJ1241. Curs acadèmic: 2019/2020This document presents the Final Report of the Video Game Design and Development project. The work consists of creating an AI with the ANN (Artificial Neural Network) method, to face the player in different game modes and then training as best as possible with the Reinforcement learning method. Then, we will introduce our AI into different game environments the player may encounter. All this can be done using the Unity game engine

Artificial Neural Networking and Human Brain

Neural Network technology performs “intelligent” tasks. ANN(Artificial Neural Network) can be employed to solve a wide spectrum of problems as optimization , Parallel Computing , Matrix Algebra and Signal Processing . ANN is an information processing paradigm inspired by the way biological nervous System , such as brain , process information ANN is an interconnected web of neurons which a building block of neural network . Neurons receives inputs from other sources, combines them in some way performs a generally non linear operation and then outputs the final results. This paper gives overview of working of Neurons for basic understanding how electronic model of ANN are work for problem solving

Plant Recognition using Hog and Artificial Neural Network

This paper presents a plant leaf recognition system being implemented through Artificial Neural Networks. The system proposed is designed using MATLAB Software which takes a leaf image from the user and classifies, recognizes the plant species and shows all the relevant details about the plant.it also incorporates a webpage from various plant databases. The leaf features are extracted by using a HOG (Histograms of Oriented Gradients) vector and the ANN(Artificial Neural Network) is used in training through Backpropagation. We have extracted the HOG features from the flavia datasheet of leaves and trained them in the Neural Network. The results were nearly perfect and the accuracy of the program implemented is very high compared with other models

An attempt at modelling the periphyton dynamics with artificial neural networks exemplified by the oxbow lake reopening study (The Słupia River, Northern Poland)

An experiment was performed in the Osokowy Staw oxbow lake (the Słupia River, northern Poland). The old riverbed was reconnected with the riverine system and periphyton communities on nylon artificial substrate were surveyed before and after engineering works. Then, ANN (Artificial Neural Network) architectures were designed and trained in order to create models of interactions between 18 macrozooperiphyton, microzooperiphyton and phytoperiphyton taxa in the changing ecosystem. Calculations were performed using StatSoft Software Statistica 6.1 with the implemented neural network module.Neural network models allowed a quantitative insight into periphyton dynamics and indicated trophic relationships, both predatoryprey and competitive. Thus, we see ANN as a good technique for modelling multidimensional, nonlinear relations between epiphytic organisms and as a promising method for creating overall models

Steady state and dynamic response of a state space observer based PMSM drive with different controllers

This paper deals with an investigation and evaluation of the performance of a state observer based Permanent Magnet Synchronous Motor (PMSM) drive controlled by PI (Proportional Integral), PID (Proportional Integral and Derivative), SMC (sliding mode control), ANN (Artificial neural network) and FLC (Fuzzy logic) speed controllers. A detailed study of the steady state and dynamic performance of estimated speed and angle is given to demonstrate the capability of the controllers