Nasir Ayub

Nasir Ayub
National University of Sciences & Technology

PhD (Computer Science)

About

32
Publications
9,141
Reads
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148
Citations
Introduction
PhD Scholar at SEECS, NUST University Islamabad. Research interests include; Natural Language Processing, Energy management, Data Science. www.nasirayub.com
Additional affiliations
February 2017 - present
COMSATS University Islamabad
Position
  • Student
Education
October 2020 - October 2024
National University of Science and technology islamabad
Field of study
  • Data Science

Publications

Publications (32)
Article
Full-text available
The smart grid has given users the ability to regulate their home energy more efficiently and effectively. Home Energy Management (HEM) is a difficult undertaking in this regard, as it necessitates the optimal scheduling of smart appliances to reduce energy usage. In this research, we introduced a meta-heuristic-based HEM system in this research, w...
Article
Full-text available
One of the major concerns for the utilities in the Smart Grid (SG) is electricity theft. With the implementation of smart meters, the frequency of energy usage and data collection from smart homes has increased, which makes it possible for advanced data analysis that was not previously possible. For this purpose, we have taken historical data of en...
Article
Full-text available
The advent of the new millennium, with the promises of the digital age and space technology, favors humankind in every perspective. The technology provides us with electric power and has infinite use in multiple electronic accessories. The electric power produced by different sources is distributed to consumers by the transmission line and grid sta...
Article
Full-text available
The population is increasing rapidly, due to which the number of vehicles has increased, but the transportation system has not yet developed as development occurred in technologies. Currently, the lowest capacity and old infrastructure of roads do not support the amount of vehicles flow which cause traffic congestion. The purpose of this survey is...
Article
Full-text available
Medium-term electricity consumption and load forecasting in smart grids is an attractive topic of study, especially using innovative data analysis approaches for future energy consumption trends. Loss of electricity during generation and use is also a problem to be addressed. Both consumers and utilities can benefit from a predictive study of elect...
Article
Full-text available
Enhanced metering infrastructure is a key component of the electrical system, offering many advantages, including load management and demand response. However, several additional energy theft channels are introduced by the automation of the metering system. With data analysis techniques, adapting the smart grid significantly reduces energy theft lo...
Article
Full-text available
Cloud Computing (CC) is a promising technology due to its pervasive features, such as online storage, high scalability, and seamless accessibility, in that it plays an important role in reduction of the capital cost and workforce, which attracts organizations to conduct their businesses and financial activities over the cloud. Even though CC is a g...
Article
Full-text available
The 2019 novel coronavirus (COVID-19) originating from China, has spread rapidly among people living in other countries. According to the World Health Organization (WHO), by the end of January, more than 104 million people have been affected by COVID-19, including more than 2 million deaths. The number of COVID-19 test kits available in hospitals i...
Article
Full-text available
Sentiment analysis is one of the most prominent sub-areas of research in Natural Language Processing (NLP), where it is important to consider implicit or explicit emotions conveyed by review material. Researchers also recognized that the generic feelings derived from the textual material are insufficient, so the sentiment analysis aspect based was...
Article
Full-text available
Cloud computing is rapidly taking over the information technology industry because it makes computing a lot easier without worries of buying the physical hardware needed for computations, rather, these services are hosted by companies with provide the cloud services. These companies contain a lot of computers and servers whose main source of power...
Article
Full-text available
Electrical load forecasting provides knowledge about future consumption and generation of electricity. There is a high level of fluctuation behavior between energy generation and consumption. Sometimes, the energy demand of the consumer becomes higher than the energy already generated, and vice versa. Electricity load forecasting provides a monitor...
Article
Full-text available
Electrical load forecasting provides knowledge about future consumption and generation of electricity. There is a high level of fluctuating than behavior between energy generation and consumption. Sometimes, the energy demand of the consumer becomes higher than the energy already generated and vice versa. Electricity load forecasting provides a mon...
Conference Paper
Full-text available
Besides the non-technical losses of power companies, theft of electricity is the most serious and dangerous one. The fraudulent power consumption degrades the quality of supply and increases the energy generation that impacts the whole grid system, which causes legitimate the users to pay a huge amount of electricity bills. Through data analysis me...
Article
Full-text available
Forecasting the electricity load provides its future trends, consumption patterns and its usage. There is no proper strategy to monitor the energy consumption and generation; and high variation among them. Many strategies are used to overcome this problem. The correct selection of parameter values of a classifier is still an issue. Therefore, an op...
Conference Paper
Full-text available
In the last few years, carbon emissions and energy demand have increased dramatically around the globe due to a surge in population and energy-consuming devices. The integration of renewable energy resources (RERs) in a power supply system provides an efficient solution in terms of low energy cost with lower carbon emissions. However, renewable sou...
Chapter
Full-text available
The present strategies for the prediction of price and load may be difficult to deal with huge amount of load and price data. To resolve the problem, three modules are incorporated within the model. Firstly, the fusion of Decision Tree (DT) and Random Forest (RF) are used for feature selection and to remove the redundancy among feature. Secondly, R...
Chapter
Full-text available
One of the key issues in the Smart Grid (SG) is accurate electric load forecasting. Energy generation and consumption have highly varying. Accurate forecasting of electric load can decrease the fluctuating behavior between energy generation and consumption. By knowing the upcoming electricity load consumption, we can control the extra energy genera...
Thesis
Full-text available
Energy is the most needed commodity of the current era. Recently, the energy demand is far higher than the available energy. Moreover, generation and consumption of energy shows fluctuating behavior. By the incorporation of Demand Side Management (DSM) with the Smart Grid (SG) and forecasting the load results in the solution of this problem. Differ...
Chapter
Full-text available
Energy is the most needed commodity of the current era. Recently, the demand of energy is far higher than the available energy. By the incorporation of Demand Side Management (DSM) with the Smart Grid (SG) results in the solution of this problem. Different techniques are utilized in SG to minimize the electricity cost and manage load in industrial,...
Conference Paper
Full-text available
In this paper, appliance scheduling scheme is proposed for residential area. Different types of heuristic and meta-heuristic optimization techniques are being used to solve the general problem of electricity demand. In this paper, a unique swarm based optimization technique Elephant Herding Optimization (EHO) is used to manage the electricity deman...
Conference Paper
Smart grid based energy management system promises an efficient consumption of electricity. For optimized energy consumption, a bio inspired meta-heuristic algorithms: Earth Worm Algorithm (EWA) and Bacterial Foraging Algorithm (BFA) are presented in this paper. In this work, we targeted residential area. Our aim is to reduce the electricity cost a...
Conference Paper
Full-text available
Energy consumption demand is comparatively higher than available energy, new approaches are being discovered to fulfill energy demand. This problem can be solved by assimilating Demand Side Management (DSM) with Smart Grid (SG). In this work, we observe the working of Home Energy Management System (HEMS) by using three meta-heuristic techniques; Ha...
Conference Paper
In this study, problem of scheduling of appliances in Home Energy Management System (HEMS) is analyzed and a solution is proposed. Although there are many heuristic algorithms for solving the scheduling problem however we considered a swarm based heuristic algorithm Elephant Herding Optimisation (EHO). EHO uses the herding behaviour of elephants to...
Conference Paper
Nowadays, Energy become the most valued necessity. Energy crisis becomes a critical issue of this era. Energy demand is increasing day by day, due to which peak load creation occurs. In order to handle the critical situation of the energy crisis, many techniques and methods are implemented. This can be done by replacing the traditional grid with sm...
Conference Paper
In this paper, appliance scheduling scheme is proposed for residential area.different types of heuristic and meta-heuristic optimization techniques are being used to solve the general problem of electricity demand. in this paper, a unique swarm based optimization technique Elephant Herding Optimization (EHO) is used to manage the electricity demand...
Conference Paper
Full-text available
Smart grid based energy management system promises an efficient consumption of electricity. For optimized energy consumption, a bio inspired meta-heuristic algorithms: Earth Worm Algorithm (EWA) and Bacterial Foraging Algorithm (BFA) are presented in this paper. In this work, we targeted residential area. Our aim is to reduce the electricity cost a...
Conference Paper
In this study, problem of scheduling of appliances in Home Energy Management System (HEMS) is analyzed and a solution is proposed. Although there are many heuristic algorithms for solving the scheduling problem however we considered a swarm based heuristic algorithm Elephant Herding Optimisation (EHO). EHO uses the herding behaviour of elephants to...
Conference Paper
Full-text available
Energy consumption demand is comparatively higher than available energy , new approaches are being discovered to fulfill energy demand. This problem can be solved by assimilating Demand Side Management (DSM) with Smart Grid (SG). In this work, we observe the working of Home Energy Management System (HEMS) by using three meta-heuristic techniques; H...
Conference Paper
Full-text available
Nowadays, Energy become the most valued necessity. Energy crisis becomes a critical issue of this era. Energy demand is increasing day by day, due to which peak load creation occurs. In order to handle the critical situation of the energy crisis, many techniques and methods are implemented. This can be done by replacing the traditional grid with sm...

Questions

Question (1)
Question
How can we combine/Embed the Machine Learning with Blockchain. Or any ML application that can be run over the machine learning chain.
or is it possible to make a machine learning chain.
or some relevant work suggestion?

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