Welcome to iRepository UNITEN

iRepository is an institutional research repository for Universiti Tenaga Nasional (UNITEN).

The purpose of an institutional repository system at UNITEN (Universiti Tenaga Nasional) is to establish a digital platform that enables the university to collect, preserve, and share its scholarly and intellectual outputs. This centralized repository serves as a hub where UNITEN can store and make openly accessible various types of content, including research articles, theses, conference papers, datasets, and multimedia materials. By implementing an institutional repository system, UNITEN aims to promote open access to knowledge, facilitate research collaboration, enhance the visibility and impact of its research outputs, and ensure the long-term preservation of the university's intellectual assets.

 
Research outputs
22582
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Recent Additions
  • Publication
    Investigation and modelling of building energy management system for sustainable energy usage
    (2018)
    Wan Muhammad Hafiz Wan Rosdi
    Energy is always an important key to developing countries such as Malaysia. A stable and secured energy supply greatly supports economic growth and ensures the living quality of all citizens. Continuous effort has been made to increase the energy supply through renewable energy sources. However, the positive effect of this effort would not be optimized without ensuring an efficient utilization of the generated energy. Therefore, this project proposes is to investigate and modelling of building energy management system for sustainable energy usage for the College of Engineering (COE), Universiti Tenaga Nasional (UNITEN) building. The Quick Energy Simulation Tool (EQUEST) will be utilized to compare the energy consumption of the building before and after the implementation of the optimized algorithm to achieve a nearly zero energy building. Smart lighting system will be the main component under this simulation tool. In this investigation and model development, energy saving, carbon reduction and cost-benefit models will be developed for sustainable building energy usages. The optimized algorithm will be implemented in the innovated features of the building towards nearly zero energy building. Accordingly, a guideline and policy recommendation will be provided for future sustainable energy building implementation. It is anticipated that, by implementing the fully developed model and algorithm, there will be at least a minimum of 30% energy saving and 25% of CO2 reduction.
  • Publication
    Optimal load shedding in power system using back tracking search algorithm
    (2015)
    Zulfadlizan Mohd
    Voltage stability is the most important things for a secure power system operation. A plenty of works have been developed to prevent voltage instability. This thesis presents a technique for optimal load shedding in power systems and a study on voltage stability. The main objective of this thesis is to develop an algorithm using MATLAB software to improve voltage stability by using load shedding process. Back tracking search algorithm is used to find the optimum loads to be shed. Contingency cases made by increasing loading using power flow method. Fast Voltage Stability Index (FVSI) and Voltage Collapse Power Indicator (VCPI) are in used to analyse the power flow continuation. The IEEE-14 bus system is simulated to analyse the power flow of the system by increasing the loads. This project have two phases, where the first phase consists literature review on voltage stability, voltage collapse, under voltage load shedding and back tracking search algorithm while the next phase are the development, testing and comparison of the algorithm with the manual calculation. The results indicate the minimum total amount of available load to be shed to make the system back to voltage stability region.
  • Publication
    Design acceleration response spectra behavior of different structural system under seismic actions
    (2013)
    Ebrahim Abdulmalek Abdulrahman Al-Qalisi
    Many study focus on earthquake design response spectra and they mostly focus on the effect of the spectra parameters, however the study presented here focus on the effect of the structural system effect on the coded design acceleration response. This study examines the seismic behavior four buildings constructed or being constructed in different parts of Malaysia, however the geological conditions and ground motion parameters are taken to be fixed to the four building as the main concern here is about the ductility and statical systems of the four buildings. The buildings were modeled and analyzed using Csc Orion software and their fundamental time was obtained through eigenvalue analysis. These results are further processed to obtain design accelerations. The study shows that the EC8 code is very conservative especially when being compared against UBC97 code. Besides, it raises the effect of having dual statical system and how such structure behave under dynamic actions. The study also discusses how the fundamental time of building; time of oscillation, is effected by the structural system and building ductility, and how this time plays an effect on the design acceleration. In the study, a good mathematical correlation and relationship of building height and design acceleration is inferred as well as a suggested formula is presented that relate the EC8 and UBC97 to each other. The building studied were found to able to resist the seismic action as they have a good ductility and actions were not significant due to the Malaysian terrain is not highly earthquake hazardous.
Most viewed
  • Publication
    Improving SVM-based nontechnical loss detection in power utility using the fuzzy inference system
    (2011)
    Nagi J.
    ;
    Yap K.S.
    ;
    Tiong S.K.
    ;
    Ahmed S.K.
    ;
    Nagi F.
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    25825455100
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    24448864400
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    15128307800
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    25926812900
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    56272534200
    This letter extends previous research work in modeling a nontechnical loss (NTL) framework for the detection of fraud and electricity theft in power distribution utilities. Previous work was carried out by using a support vector machine (SVM)-based NTL detection framework resulting in a detection hitrate of 60%. This letter presents the inclusion of human knowledge and expertise into the SVM-based fraud detection model (FDM) with the introduction of a fuzzy inference system (FIS), in the form of fuzzy if-then rules. The FIS acts as a postprocessing scheme for short-listing customer suspects with higher probabilities of fraud activities. With the implementation of this improved SVM-FIS computational intelligence FDM, Tenaga Nasional Berhad Distribution's detection hitrate has increased from 60% to 72%, thus proving to be cost effective. � 2011 IEEE.
  • Publication
    Implementation of data intelligence models coupled with ensemble machine learning for prediction of water quality index
    (Springer Science and Business Media Deutschland GmbH, 2020)
    Abba S.I.
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    Pham Q.B.
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    Saini G.
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    Linh N.T.T.
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    Ahmed A.N.
    ;
    Mohajane M.
    ;
    Khaledian M.
    ;
    Abdulkadir R.A.
    ;
    Bach Q.-V.
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    57208942739
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    57208495034
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    57197592021
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    57211268069
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    57214837520
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    57195618368
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    23089044300
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    57200567560
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    23033338600
    In recent decades, various conventional techniques have been formulated around the world to evaluate the overall water quality (WQ) at particular locations. In the present study, back propagation neural network (BPNN) and adaptive neuro-fuzzy inference system (ANFIS), support vector regression (SVR), and one multilinear regression (MLR) are considered for the prediction of water quality index (WQI) at three stations, namely Nizamuddin, Palla, and Udi (Chambal), across the Yamuna River, India. The nonlinear ensemble technique was proposed using the neural network ensemble (NNE) approach to improve the performance accuracy of the single models. The observed WQ parameters were provided by the Central Pollution Control Board (CPCB) including dissolved oxygen (DO), pH, biological oxygen demand (BOD), ammonia (NH3), temperature (T), and WQI. The performance of the models was evaluated by various statistical indices. The obtained results indicated the feasibility of the developed data intelligence models for predicting the WQI at the three stations with the superior modelling results of the NNE. The results also showed that the minimum values for root mean square�(RMS) varied between 0.1213 and 0.4107, 0.003 and 0.0367, and 0.002 and 0.0272 for Nizamuddin, Palla, and Udi (Chambal), respectively. ANFIS-M3, BPNN-M4, and BPNN-M3 improved the performance with regard to an absolute error by 41%, 4%, and 3%, over other models for Nizamuddin, Palla, and Udi (Chambal) stations, respectively. The predictive comparison demonstrated that NNE proved to be effective and can therefore serve as a reliable prediction approach. The inferences of this paper would be of interest to policymakers in terms of WQ for establishing sustainable management strategies of water resources. � 2020, Springer-Verlag GmbH Germany, part of Springer Nature.
  • Publication
    Mechanics II: Dynamics - CMPF 112 - Trimester 1, 2015/2016
    (2015-09)
    College of Foundation and Diploma Studies
  • Publication
    Business analytics - CISB 474 - Semester 1, 2018/2019
    (2018-09)
    College of Computer Science and Information Technology
  • Publication
    International marketing - MKEB 333 - Semester 2, 2016/2017
    (2017-01-23)
    College of Business Management and Accounting