Pusat Pengajian Informatik dan Matematik Gunaan
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Item TERENGGANU’S RAINFALL TIME SERIES ANALYSIS USING HIERARCHICAL AGGLOMERATIVE CLUSTERING BASED ON DYNAMIC TIME WARPING AND PERSISTENT HOMOLOGY(Universiti Malaysia Terengganu, 2023-07) KIRTHANA DEVI A/P SELVARAJHItem DECISION-MAKING UNDER PYTHAGOREAN FUZZY VAGUE SETS ENVIRONMENT AND APPLICATION(Universiti Malaysia Terengganu, 2023) WAN ROSANISAH WAN MOHDItem ON FUZZY TOPOLOGICAL DIGITAL RELATION SPACE AND FUZZY B-SPLINE DIGITAL MODEL FOR UNCERTAINTY DATA(Universiti Malaysia Terengganu, 2023) MAZLINA MUZAFAR SHAHItem DEVELOPMENT OF TIME-WEIGHTED CONTROL CHARTS BASED ON INTERVAL TYPE-2 FUZZY SETS(Universiti Malaysia Terengganu, 2023-09) NUR HIDAYAH MOHD RAZALIItem MODELING AND QUALITATIVE ANALYSIS OF TYPE-2 DIABETIC POPULATION WITH DELAY DIFFERENTIAL EQUATIONS(Universiti Malaysia Terengganu, 2023) MUHAMAD HANIS BIN MOHD NASIRItem STOCHASTICMODELLINGOFTEMPERATUREVARIATIONSWITH APPLICATIONTOFINANCEANDINSURANCE(Universiti Malaysia Terengganu, 2022) MUKMINAHBINTIDARUSItem DECISION-MAKING METHODS UNDER INTERVAL-VALUED INTUITIONISTIC FUZZY VAGUE SET ENVIRONMENT & APPLICATIONS(Universiti Malaysia Terengganu, 2021) NORSYAHIDA BT ZULKIFLIItem CLOUD COMPUTING BASED MOBILE LEARNING FRAMEWORK FOR JORDANIAN HIGHER EDUCATION INSTITUTIONS(Universiti Malaysia Terengganu, 2023) MARWAN ATOOMItem NETWORK SCALABILITY AND GATEWAYS POSITIONING USING GENETIC ALGORITHM FOR LOW POWER WIDE AREA NETWORK(Universiti Malaysia Terengganu, 2023) IDRUS SALIMI BIN ISMAILItem IMPACT OF AUXILIARY LINES ON VORTEX-INDUCED VIBRATION OF A DRILLING RISER SYSTEM(Universiti Malaysia Terengganu, 2023-04) FATIN BINTI ALIASItem Modification of Steepest Descent Method for Solving Unconstrained Optimization(Universiti Malaysia Terengganu, 2014-03) Zubai'dah Binti Zainal AbidinThe Classical steepest descent (SD) method is known as one of the earliest and the best method to minimize a function. Even though the convergence rate is quite slow, but its simplicity has made it one of the easiest methods to be used and applied especially in the form of computer codes.Item Hoff Bifurcation Analysis on Nonlinear Dynamical Systems(Universiti Malaysia Terengganu, 2014-08) Tee Loong SoonDynamical systems have been very prominent for their various functions in real life, for instance in the population growth model. There have been many researched systems such as the Liu system, Chen system, Lu system, Qi system and Zhou system that have been studied intensively. Our main research here is on a modified Lorenz system.Item Linear Programming Technique In Zebrafish Feed Formulation For A Better Growth And Colour Enhancement(Universiti Malaysia Terengganu, 2020) Ibrahim, Rabiatul AdawiyahFeed formulation is a combination of different ingredients with variety of nutrients to formulate a type of food that contains complete nutrient needed by living things. It is to ensure that they receive enough nutrients for their healthy growth and survival. In aquaculture field, major concerns among aquaculture nutrition researchers only focus on the growth and survival of the fish but neglecting the cost of feed production. The conventional method in formulating fish feed is often time-consuming, expensive and species dependence. Early mathematics researchers had attempted to solve diet formulation problem with mathematical modelling. Mathematical model is an approach that can provide precise composition required in fish feed with aquaculture knowledge as background, which can provide precise nutrient requirement depends on specific species and minimizes the cost of operation when compared to the use of commercial pellet. Early researchers have applied mathematical modelling in formulating feed and took a long time to obtain a complete feed if hand-operated desk calculators are used. Transition of modern era leads to highly sophisticated computer systems that simplifies the complicated problem involved in feed formulation problem. However, the research about application of mathematics modelling in aqua feed especially for ornamental fish, which centred on reducing feed production cost and alternative ingredients replacement are hard to be found in Malaysia.Item Ranking Fuzzy Numbers Using Centerbased Methods And Its Application(Universiti Malaysia Terengganu, 2014-02) Fateen Najwa Binti AzmanRanking fuzzy numbers has become an important process in decision making. Many ranking methods have been proposed thus far and one of the commonly used is centroid method. However, there is still no agreement on the method that can always provide a satisfactory solution to every situation. This research aims to propose a new ranking fuzzy numbers method using circumcenter, orthocenter and incenter of centroids. The calculation for the circumcenter, orthocenter and incenter is derived from a trapezoidal of fuzzy numbers which is split into three parts of triangle and series of proposed algorithms. The new proposed algorithms not only compute the center- based, but also consider the height, distance, spread and area of trapezoidal fuzzy numbers. An implementation of the proposed algorithms in a few examples of ranking fuzzy numbers and decision making problem is given to illustrate the proposed methods. In order to test the proposed methods in real cases, a case study of risk analysis on obesity is used and the results show that the factor of family history is the main factors that contribute to obesity. The result implicates the importance of family’s lifestyle in minimising the development of obesity.Item Perbandingan Di Antara Model Regresi Logistik Dan Model Rangkaian Neural Terhadap Obesiti: Kajian Kes Pesakit Kencing Manis Jenis Kedua(Universiti Malaysia Terengganu, 2014-01) Tengku Nurhanis Binti Tengku AdliObjektif kajian ini ialah untuk membina model Regresi Logistik dan model Rangkaian Neural, untuk membandingkan dan mengenalpasti model ramalan terbaik (model Regresi Logistik dan model Rangkaian Neural) untuk meramalkan obesiti dan untuk mengenalpasti pembolehubah penting (faktor- faktor) yang mempengaruhi obesiti. Data primer dikumpulkan daripada klinik kencing manis di HUSM, Kota Bharu (KB), Kelantan. Kajian ini menggunakan perisian SPSS Clementine versi 12.0 untuk membina model. Daripada kajian ini, model terakhir yang digunakan untuk meramalkan obesiti adalah kaedah Prun di dalam model Rangkaian Neural, kerana ia mempunyai nilai kadar ralat terendah iaitu 0.1094 (10.94%), nilai kepekaan tertinggi iaitu 0.9298 (92.98%) dan nilai ketentuan tertinggi iaitu 0.5714 (57.14%); manakala pembolehubah penting/faktor yang mempengaruhi obesiti ialah berat badan.Item Perbandingan Di Antara Model Regresi Logistik Dan Model Rangkaian Neural Terhadap Obesiti: Kajian Kes Pesakit Kencing Manis Jenis Kedua(Universiti Malaysia Terengganu, 2014-01) Tengku Nurhanis Binti Tengku AdliObjektif kajian ini ialah untuk membina model Regresi Logistik dan model Rangkaian Neural, untuk membandingkan dan mengenalpasti model ramalan terbaik (model Regresi Logistik dan model Rangkaian Neural) untuk meramalkan obesiti dan untuk mengenalpasti pembolehubah penting (faktor- faktor) yang mempengaruhi obesiti. Data primer dikumpulkan daripada klinik kencing manis di HUSM, Kota Bharu (KB), Kelantan. Kajian ini menggunakan perisian SPSS Clementine versi 12.0 untuk membina model. Daripada kajian ini, model terakhir yang digunakan untuk meramalkan obesiti adalah kaedah Prun di dalam model Rangkaian Neural, kerana ia mempunyai nilai kadar ralat terendah iaitu 0.1094 (10.94%), nilai kepekaan tertinggi iaitu 0.9298 (92.98%) dan nilai ketentuan tertinggi iaitu 0.5714 (57.14%); manakala pembolehubah penting/faktor yang mempengaruhi obesiti ialah berat badan.Item Development Of Fuzzy Topsis System For Measuring Human Well-Being(Universiti Malaysia Terengganu, 2014-01) Rosilawati Binti OthemanThese days, systems in the multi-criteria decision making (MCDM) method are important. Systems are created to solve problems in order to help users solve mathematical problems faster, easier and more accurate. This research is aimed at developing a fuzzy TOPSIS system (FTS) for measuring human well-being, which uses objective weights to rank of four alternatives. MCDM is widely used in ranking one or more sets of available alternatives, with respect to multiple criteria. Three main objectives are presented in this research. The first objective is to develop a system of weights of human well-being criteria using the fuzzy TOPSIS method with a confidence level. This system usesthe Microsoft Visual Basic 2008 Express Edition software to develop a fuzzy TOPSIS method.Item Development Of Fuzzy Topsis System For Measuring Human Well-Being(Universiti Malaysia Terengganu, 2014-01) Rosilawati Binti OthemanThese days, systems in the multi-criteria decision making (MCDM) method are important. Systems are created to solve problems in order to help users solve mathematical problems faster, easier and more accurate. This research is aimed at developing a fuzzy TOPSIS system (FTS) for measuring human well-being, which uses objective weights to rank of four alternatives. MCDM is widely used in ranking one or more sets of available alternatives, with respect to multiple criteria. Three main objectives are presented in this research. The first objective is to develop a system of weights of human well-being criteria using the fuzzy TOPSIS method with a confidence level. This system uses the Microsoft Visual Basic 2008 Express Edition software to develop a fuzzy TOPSIS method.Item Integration Of Interval Type-2 Fuzzy Saw And Interval Type-2 Fuzzy Topsis For Ambulance Location Selection(Universiti Malaysia Terengganu, 2015-04) C. W. Rabiatul Adawiyah C. W. KamalNowadays, Multi Criteria Decision Making (MCDM) methods are widely utilized and known as effective tools in solving real world problems. Various MCDM methods have been implemented in solving diverse applications of decision problems. One of the MCDM methods is additive weighting-based method. Unfortunately, this method is not always applicable due to the limitations in computational reliability and its applications are not-well received by many MCDM enthusiasts. The method is extended to Fuzzy Simple Additive Weighting (Fuzzy SAW) thanks to the development of fuzzy set theory. Fuzzy SAW utilized fuzzy numbers rather than crisp numbers. Nevertheless, type-1 fuzzy set is weak in handling uncertainty compared to Interval Type-2 Fuzzy Set (IT2 FS). Differently from the typical Fuzzy SAW, which directly utilized trapezoidal type-1 fuzzy numbers, IT2 FS introduced to the Fuzzy SAW to enhance judgments in the fuzzy decision making environment. IT2 FS is more sensitive in handling uncertain information or data. Besides, in this study, Interval Type-2 Fuzzy Simple Additive ii Weighting (IT2 Fuzzy SAW) method is integrate with Interval Type-2 Fuzzy Technique for Order Preference by Similarity to Ideal Solution (IT2 Fuzzy TOPSIS) method to handle fuzzy multiple criteria decision making problems based on IT2 FSs.Item Saw And Interval Type-2 Fuzzy Topsis For Ambulance Location Selection(Universiti Malaysia Terengganu, 2015-04) C. W. Rabiatul Adawiyah C. W. KamalNowadays, Multi Criteria Decision Making (MCDM) methods are widely utilized and known as effective tools in solving real world problems. Various MCDM methods have been implemented in solving diverse applications of decision problems. One of the MCDM methods is additive weighting-based method. Unfortunately, this method is not always applicable due to the limitations in computational reliability and its applications are not-well received by many MCDM enthusiasts. The method is extended to Fuzzy Simple Additive Weighting (Fuzzy SAW) thanks to the development of fuzzy set theory. Fuzzy SAW utilized fuzzy numbers rather than crisp numbers. Nevertheless, type-1 fuzzy set is weak in handling uncertainty compared to Interval Type-2 Fuzzy Set (IT2 FS). Differently from the typical Fuzzy SAW, which directly utilized trapezoidal type-1 fuzzy numbers, IT2 FS introduced to the Fuzzy SAW to enhance judgments in the fuzzy decision making environment. IT2 FS is more sensitive in handling uncertain information or data. Besides, in this study, Interval Type-2 Fuzzy Simple Additive ii Weighting (IT2 Fuzzy SAW) method is integrate with Interval Type-2 Fuzzy Technique for Order Preference by Similarity to Ideal Solution (IT2 Fuzzy TOPSIS) method to handle fuzzy multiple criteria decision making problems based on IT2 FSs.
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