A5033865889- Energy Load and Power Forecasting
- Hydrological Forecasting Using AI
- Hydrology and Watershed Management Studies
- Solar Radiation and Photovoltaics
- Flood Risk Assessment and Management
- Water Treatment and Disinfection
- Hydrology and Drought Analysis
- Photovoltaic System Optimization Techniques
- Wind Energy Research and Development
- Smart Agriculture and AI
- Electric Motor Design and Analysis
- Heat Transfer and Optimization
- Smart Grid and Power Systems
- Stock Market Forecasting Methods
- Railway Systems and Energy Efficiency
- Magnetic Properties and Applications
- Water Quality Monitoring Technologies
- Heat Transfer Mechanisms
- Isotope Analysis in Ecology
- Modular Robots and Swarm Intelligence
- Induction Heating and Inverter Technology
- Extraction and Separation Processes
- Power Quality and Harmonics
- Water Governance and Infrastructure
- Greenhouse Technology and Climate Control
Southeast University
2023-2024
China Three Gorges University
2020-2024
National University of Sciences and Technology
2023-2024
China Energy Engineering Corporation (China)
2024
University of the Sciences
2023
International Islamic University, Islamabad
2018-2021
University of Engineering and Technology Lahore
2018
To improve the accuracy and reliability of short-term power load forecasting reduce difficulty caused by volatility non-linearity, a hybrid model (CEEMDAN-SE-VMD-PSR-WOA-SVR) is proposed. Firstly, complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) employed to generate multiple intrinsic modal functions (IMF) decomposing historical series. Then sample entropy (SE) each IMF calculated quantitatively evaluate corresponding complexity. Afterward, variational (VMD)...
Pakistan has not fully harnessed the capacity of its vast hydropower potential for electricity generation. It depends on imported and local fossil fuels to fulfill energy demands, which consume a significant portion country's economy. Hydropower can provide an economical, renewable, clean, secure source country. The benefits prospects require comprehensive review sector investigate true resource development, considering associated pros cons. Therefore, work examines utilization in using SWOT...
Precise and reliable hydrological runoff prediction plays a significant role in the optimal management of hydropower resources. Nevertheless, practically possesses nonlinear dynamics, constructing appropriate models to deal with nonlinearity is challenging task. To overcome this difficulty, paper proposes three-stage novel hybrid model, namely, CVS (CEEMDAN-VMD-SVM), by coupling support vector machine (SVM) two-stage signal decomposition methodology, combining complete ensemble empirical...
Accuracy of solar irradiance forecasting is imperative for the effective utilization and integration energy into power system. To forecast global horizontal based on a multivariate meteorological data; this study first evaluates five standalone models, including recurrent deterministic policy gradient (RDPG), long short term memory (LSTM) neural network, extreme boosting (XGB), Gaussian process regression (GPR), support vector (SVR). The RDPG model outperforms counterparts by demonstrating...
The accuracy and consistency of streamflow prediction play a significant role in several applications involving the management hydrological resources, such as power generation, water supply, flood mitigation. However, nonlinear dynamics climatic factors jeopardize development efficient models. Therefore, to enhance reliability prediction, this paper developed three-stage hybrid model, namely, IVL (ICEEMDAN-VMD-LSTM), which integrated improved complete ensemble empirical mode decomposition...
The optimal management of hydropower resources is highly dependent on accurate and reliable hydrological runoff forecasting.The development a suitable runoff-forecasting model challenging task due to the complex nonlinear nature runoff.To meet challenge, this study proposed three-stage novel hybrid namely IVG (ICEEMDAN-VMD-GRU), by coupling gated recurrent unit (GRU) with two-stage signal decomposition methodology, combining improved complete ensemble empirical additive noise (ICEEMDAN)...
Disinfection during tertiary municipal wastewater treatment is a necessary step to control the spread of pathogens; unfortunately, it also gives rise numerous disinfection byproducts (DBPs), only few which are regulated because analytical challenges associated with vast number potential DBPs. This study utilized polydimethylsiloxane (PDMS) passive samplers, comprehensive two-dimensional gas chromatography (GC×GC) coupled time-of-flight mass spectrometry (TOFMS), and non-negative matrix...
Disinfection during tertiary municipal wastewater treatment is a necessary step to control the spread of pathogens; unfortunately, it also gives rise numerous disinfection byproducts (DBPs), only few which are regulated because analytical challenges associated with vast number potential DBPs. This study utilizes polydimethylsiloxane (PDMS) passive samplers, comprehensive two-dimensional gas chromatography (GC×GC) coupled time-of-flight mass spectrometry (TOFMS), non-negative matrix...
In this paper 17-level single and three phase multilevel inverter is developed by using 10 switches 6 direct current (DC) power supplies for each phase. The output voltage cycle comprises of all the possible combinations which give a very high value as compared to applied DC voltage. technique used in switch ladder (SLMLI) modified form H-Bridge inverter. this, conduct during step hence offers low total harmonic distortion (THD), higher efficiency greater reliability giving 17 levels. THD...
In this paper, an interior permanent magnet synchronous motor with a D-type rotor configuration is presented. The performance of the proposed compared that widely used V-type motor. For fair comparison, all parameters are identical. With advent different topologies, multilayered and multisegmented magnets extensively used; however, analytical modeling has not yet been conducted. Furthermore, its analysis using finite element method considerably time-consuming. To resolve problem, based on...
The following topics are dealt with: Internet of Things; wireless LAN; learning (artificial intelligence); smart power grids; sensor networks; environmental science computing; mobile pattern clustering; health care; quality service.
Abstract In this study, 03 ensemble and decomposition methods (DMs) i.e., empirical mode (EMD), (EEMD) improved complete with additive noise (ICEEMDAN) were coupled artificial intelligence machine learning based method AI-ML, multilayer perceptron (MLP), support vector regression (SVR) to develop 06 fundamental hybrid models predict streamflow one-month lead time. Developed in study categorized into runoff (RMs) rainfall-runoff (RRMs). Results indicated that (i) among standalone (SMs),...
Waste heat recovery technologies from engine exhaust are promising solutions for increasing energy efficiency, reducing fuel consumption, and decreasing greenhouse gas emissions. Heat exchangers play a crucial role in waste exhaust. In this study, numerical simulation was carried out to investigate the performance of counter shell tube exchanger with without inner fin geometry. A CFD analysis showed that addition fins improved transfer exchanger. Further, use GO/water nanofluid is effective...