Articles published in IJEER


Fuzzy and ANFIS Controllers to Improve the Power Quality of Grid Connected PV System with Cascaded Multilevel Inverter

In this paper, A Cascaded Multi level Inverter (CMLI) interconnected with the 10 KW PV System, Boost Converter along with Cascaded Feed Forwarded Neural Network (CFFNN) MPPT Controller is proposed to improve the Power Quality (PQ) for Linear, Non-linear and unbalanced loading conditions and minimize the total Harmonic Distortion (THD). The CMLI Consists of Novel type 9-Level Inverter with Reduced number of switches, and is connected to Bridged type inverter as cascaded, to get the required amount of Output voltage which can be used for grid integration.

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Development of DSTATCOM Optimal Sizing and Location Technique Based on IA-GA for Power Loss Reduction and Voltage Profile Enhancement in an RDN

In this paper, an innovative technique based on hybridized Immune and Genetic Algorithm (IA-GA) for optimal DSTATCOM placement and sizing for three distinct load levels is proposed. Simulation and analysis of the proposed algorithm were carried out using IEEE-33 bus radial distribution network (RDN) in MATLAB. The simulation results demonstrate a substantial decrease in power loss and a significant improvement in the voltage profile. Evaluation of the proposed method against existing techniques reveals that the proposed technique outperforms IA and PSO in terms of decreasing power loss and enhancement of voltage profiles. A cost-benefit analysis was performed, and it was discovered that the proposed technique yields improved annual cost savings.

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REULEAUX Triangle Shaped MSPA for 5G and WLAN Applications

This research work proposes a low-key Reuleaux Triangle Shaped antenna having a square, rectangular Patch attached through the feedline. This antenna has Reuleaux Triangle as a patch element with a bottom having square-shaped geometry to attain ultra-wideband characteristics. This compact wideband antenna for WLAN, 5G and WiMAX applications has been presented in this manuscript.

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Electrical Load Forecasting using ARIMA, Prophet and LSTM Networks

Forecasting electrical load plays a vital role in power system planning. However, it is quite difficult to forecast electrical load, as the load on the system varies continuously concerning time and seasons. In this paper, we are proposing an advanced artificial neural network model to forecast short-term electrical load. The proposed method tested on historical data collected from Karnataka power corporation, India, and test results compared with other data-driven models viz. ARIMA, RNN, LSTM, and Prophet. The accuracy and RMSE values were calculated and observed that the proposed model was superior in a day and weekly ahead electrical load forecasting.

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Smart Heart Disease Detection using Particle Swarm Optimization and Support Vector Machine

Healthcare and disease detection in early stage is important in every human being. Proper and optimum detection of disease with smart controller is done using Particle swarm optimization (PSO) and Support Vector Machine (SVM). The research includes the Fuzzy Proportional Integral and Derivative (Fuzzy PID) controller was used with support vector machine to classify the heart disease. Particle Swarm Optimization is designed to remove the noise introduced in Electrocardiogram signal. Fuzzy PID controller was implemented for disease detection and prediction. Fuzzy PID controller provides most accurate and stable results.

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An Integrated Fundus Image Segmentation Algorithm for Multiple Eye Ailments

The detection of eye illnesses requires a thorough inspection of all of the eye's structures. Most significantly, the presence of blood vessels, an optical disc, and any other unwelcome objects, if any are discovered, is critical in determining the type of eye disease present. Specifically, the goal of this research is to establish a thorough segmentation framework that will aid in the detection of anatomical anomalies in the eye. A novel segmentation technique for analyzing blood vessels, optical disc health, and the presence of exudates has been added into the software.

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Modelling of Electric Vehicle with PID Controller Transfer Function using GA and Model-Reduced Order DRA Algorithm

In this paper, a model of an electric vehicle transfer function using GA and a model-reduced order discrete time realization (DRA) algorithm is presented. The electric vehicle (EV) control system regulates vehicle speed according to the driver’s command signal and brings the vehicle to its equilibrium point, i.e., the desired speed under any abnormal conditions. The controller transfer function is designed based on EV's dynamic differential equations. An infinite-order transcendental transfer function for the EV model is approximated to find high-reliability discrete-time state-space reduced-order models (ROMs).

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Contrast Enhancement of Colour Images by Optimized Fuzzy Intensification

Contrast enhancement is a critical and difficult issue because inappropriate enhancement by existing global image enhancement techniques might result in over or under enhancement. Varying areas of the image that are lighted indicate different shades and contrast in the output images. Projected technique uses local colour correction in the Hue Saturation Luminance (HSL) colour space. To control colour fidelity in initial phase an optimized fuzzy intensification parameters are extracted automatically form fuzzy inference system for that particular image.

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