Search results for: probabilistic neural network

Authors: Lihui Ma, Kunlun Xin, Suiqing Liu

Abstract:

Modern managements of water distribution system (WDS) need water quality models that are able to accurately predict the dynamics of water quality variations within the distribution system environment. Before water quality models can be applied to solve system problems, they should be calibrated. Although former researchers use GA solver to calibrate relative parameters, it is difficult to apply on the large-scale or medium-scale real system for long computational time. In this paper a new method is designed which combines both macro and detailed model to optimize the water quality parameters. This new combinational algorithm uses radial basis function (RBF) metamodeling as a surrogate to be optimized for the purpose of decreasing the times of time-consuming water quality simulation and can realize rapidly the calibration of pipe wall reaction coefficients of chlorine model of large-scaled WDS. After two cases study this method is testified to be more efficient and promising, and deserve to generalize in the future.

Keywords: Metamodeling, model calibration, radial basisfunction, water distribution system, water quality model.

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Authors: Chad Goldsworthy, B. Rajeswari Matam

Abstract:

The use of deep learning for species identification in camera trap images has revolutionised our ability to study, conserve and monitor species in a highly efficient and unobtrusive manner, with state-of-the-art models achieving accuracies surpassing the accuracy of manual human classification. The high imbalance of camera trap datasets, however, results in poor accuracies for minority (rare or endangered) species due to their relative insignificance to the overall model accuracy. This paper investigates the use of Focal Loss, in comparison to the traditional Cross Entropy Loss function, to improve the identification of minority species in the “255 Bird Species” dataset from Kaggle. The results show that, although Focal Loss slightly decreased the accuracy of the majority species, it was able to increase the F1-score by 0.06 and improve the identification of the bottom two, five and ten (minority) species by 37.5%, 15.7% and 10.8%, respectively, as well as resulting in an improved overall accuracy of 2.96%.

Keywords: Convolutional neural networks, data imbalance, deep learning, focal loss, species classification, wildlife conservation.

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Authors: Andrea Gelmini

Abstract:

This paper considers the advent of 5G and the use of it in a Based Control System (BCS), posing as a basic concept the question of what the real differences and practical improvements are compared to 4G. To this purpose, a testbed hardware simulator has been designed and built where identical machines with the same sensors and management systems will communicate with different radio access network connections. This allows an objective statistical comparison of performance on the real functioning and improvement of the infrastructure with the Industrial Internet of Things (IIoT) connected to it.

Keywords: 4G, 5G, BCS, eSIM, IIoT, SCADA, Testbed.

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Authors: Mehrdad Mahdavi Boroujerdi, Soheil Nazem

Abstract:

Cloud Computing is a new technology that helps us to use the Cloud for compliance our computation needs. Cloud refers to a scalable network of computers that work together like Internet. An important element in Cloud Computing is that we shift processing, managing, storing and implementing our data from, locality into the Cloud; So it helps us to improve the efficiency. Because of it is new technology, it has both advantages and disadvantages that are scrutinized in this article. Then some vanguards of this technology are studied. Afterwards we find out that Cloud Computing will have important roles in our tomorrow life!

Keywords: Cloud Computing, Grid Computing, Internet as a Platform, On-demand Computing, Software as a Service.

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Authors: Zhengnan Shi

Abstract:

In this paper, we consider the problem of Popular Matching of strictly ordered preference lists. A Popular Matching is not guaranteed to exist in any network. We propose an IDbased, constant space, self-stabilizing algorithm that converges to a Maximum Popular Matching an optimum solution, if one exist. We show that the algorithm stabilizes in O(n5) moves under any scheduler (daemon).

Keywords: self-stabilization, popular matching, algorithm, distributed computing, fault tolerance

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Authors: Niveditha Domse, Kris Kumar, K. N. Balasubramanya Murthy

Abstract:

The more recent satellite projects/programs makes extensive usage of real – time embedded systems. 16 bit processors which meet the Mil-Std-1750 standard architecture have been used in on-board systems. Most of the Space Applications have been written in ADA. From a futuristic point of view, 32 bit/ 64 bit processors are needed in the area of spacecraft computing and therefore an effort is desirable in the study and survey of 64 bit architectures for space applications. This will also result in significant technology development in terms of VLSI and software tools for ADA (as the legacy code is in ADA). There are several basic requirements for a special processor for this purpose. They include Radiation Hardened (RadHard) devices, very low power dissipation, compatibility with existing operational systems, scalable architectures for higher computational needs, reliability, higher memory and I/O bandwidth, predictability, realtime operating system and manufacturability of such processors. Further on, these may include selection of FPGA devices, selection of EDA tool chains, design flow, partitioning of the design, pin count, performance evaluation, timing analysis etc. This project deals with a brief study of 32 and 64 bit processors readily available in the market and designing/ fabricating a 64 bit RISC processor named RISC MicroProcessor with added functionalities of an extended double precision floating point unit and a 32 bit signal processing unit acting as co-processors. In this paper, we emphasize the ease and importance of using Open Core (OpenSparc T1 Verilog RTL) and Open “Source" EDA tools such as Icarus to develop FPGA based prototypes quickly. Commercial tools such as Xilinx ISE for Synthesis are also used when appropriate.

Keywords: RISC MicroProcessor, RPC – RISC Processor Core, PBX – Processor to Block Interface part of the Interconnection Network, BPX – Block to Processor Interface part of the Interconnection Network, FPU – Floating Point Unit, SPU – Signal Processing Unit, WB – Wishbone Interface, CTU – Clock and Test Unit

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Authors: Adam Roman

Abstract:

Finding synchronizing sequences for the finite automata is a very important problem in many practical applications (part orienters in industry, reset problem in biocomputing theory, network issues etc). Problem of finding the shortest synchronizing sequence is NP-hard, so polynomial algorithms probably can work only as heuristic ones. In this paper we propose two versions of polynomial algorithms which work better than well-known Eppstein-s Greedy and Cycle algorithms.

Keywords: Synchronizing words, reset sequences, Černý Conjecture

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Authors: Mert Bal, Hayri Sever, Oya Kalıpsız

Abstract:

Medical Decision Support Systems (MDSSs) are sophisticated, intelligent systems that can provide inference due to lack of information and uncertainty. In such systems, to model the uncertainty various soft computing methods such as Bayesian networks, rough sets, artificial neural networks, fuzzy logic, inductive logic programming and genetic algorithms and hybrid methods that formed from the combination of the few mentioned methods are used. In this study, symptom-disease relationships are presented by a framework which is modeled with a formal concept analysis and theory, as diseases, objects and attributes of symptoms. After a concept lattice is formed, Bayes theorem can be used to determine the relationships between attributes and objects. A discernibility relation that forms the base of the rough sets can be applied to attribute data sets in order to reduce attributes and decrease the complexity of computation.

Keywords: Formal Concept Analysis, Rough Set Theory, Granular Computing, Medical Decision Support System.

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Authors: Imran Ihsan, Muhammad Abdul Qadir, Nadeem Iftikhar

Abstract:

Mobile devices, which are progressively surrounded in our everyday life, have created a new paradigm where they interconnect, interact and collaborate with each other. This network can be used for flexible and secure coordinated sharing. On the other hand Grid computing provides dependable, consistent, pervasive, and inexpensive access to high-end computational capabilities. In this paper, efforts are made to map the concepts of Grid on Ad-Hoc networks because both exhibit similar kind of characteristics like Scalability, Dynamism and Heterogeneity. In this context we propose “Mobile Ad-Hoc Services Grid – MASGRID".

Keywords: Mobile Ad-Hoc Networks, Grid Computing, Resource Discovery, Routing

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Authors: Syed Muhammad Aqil Burney, Tahseen Ahmed Jilani, C. Ardil

Abstract:

Financial forecasting is an example of signal processing problems. A number of ways to train/learn the network are available. We have used Levenberg-Marquardt algorithm for error back-propagation for weight adjustment. Pre-processing of data has reduced much of the variation at large scale to small scale, reducing the variation of training data.

Keywords: Gradient descent method, jacobian matrix.Levenberg-Marquardt algorithm, quadratic error surfaces,

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Authors: Hasanul Ferdaus, Sazzadur Rahman, Kamrul Islam

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With the rapid usage of portable devices mobility in IP networks becomes more important issue in the recent years. IETF standardized Mobile IP that works in Network Layer, which involves tunneling of IP packets from HA to Foreign Agent. Mobile IP suffers many problems of Triangular Routing, conflict with private addressing scheme, increase in load in HA, need of permanent home IP address, tunneling itself, and so on. In this paper, we proposed mobility management in Application Layer protocol SIP and show some comparative analysis between Mobile IP and SIP in context of mobility.

Keywords: Mobility, mobile IP, SIP, tunneling.

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Authors: Abdellah Chehri, Hussein Mouftah, Paul Fortier, Hasnaa Aniss

Abstract:

Wireless sensor network has recently emerged as enablers of several areas. Real applications of WSN are being explored and some of them are yet to come. While the potential of sensor networks has been only beginning to be realized, several challenges still remain. One of them is the experimental evaluation of WSN. Therefore, deploying and operating a testbed to study the real behavior of WSN become more and more important. The main contribution of this work is to analysis the RF link budget behavior of wireless sensor networks in underground mine gallery.

Keywords: Sensor networks, RF Link, path loss.

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Authors: Yoichi Ishikawa, Yuichi Masukake, Yoshihisa Ishida

Abstract:

This paper presents a novel control method based on radial basis function networks (RBFNs) for chaotic dynamical systems. The proposed method first identifies the nonlinear part of the chaotic system off-line and then constructs a model-following controller using only the estimated system parameters. Simulation results show the effectiveness of the proposed control scheme.

Keywords: Chaos, nonlinear plant, radial basis function network.

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Authors: Seyed Saeed Changiz Rezaei, Babak Hossein Khalaj

Abstract:

As the demand for higher capacity in a cellular environment increases, the cell size decreases. This fact makes the role of suitable handoff algorithms to reduce both number of handoffs and handoff delay more important. In this paper we show that applying the grey prediction technique for handoff leads to considerable decrease in handoff delay with using a small number of handoffs, compared with traditional hystersis based handoff algorithms.

Keywords: Cellular network, Grey prediction, Handoff.

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Authors: J. Dubois, P. Jreije

Abstract:

Internet security attack could endanger the privacy of World Wide Web users and the integrity of their data. The attack can be carried out on today's most secure systems- browsers, including Netscape Navigator and Microsoft Internet Explorer. There are too many types, methods and mechanisms of attack where new attack techniques and exploits are constantly being developed and discovered. In this paper, various types of internet security attack mechanisms are explored and it is pointed out that when different types of attacks are combined together, network security can suffer disastrous consequences.

Keywords: DoS, internet attacks, router attack, security, trojan, virus, worm, XSS.

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Authors: Sh. Derakhshan, A. Mostafavi

Abstract:

Nowadays, the challenge in hydraulic turbine design is the multi-objective design of turbine runner to reach higher efficiency. The hydraulic performance of a turbine is strictly depends on runner blades shape. The present paper focuses on the application of the multi-objective optimization algorithm to the design of a small Francis turbine runner. The optimization exercise focuses on the efficiency improvement at the best efficiency operating point (BEP) of the GAMM Francis turbine. A global optimization method based on artificial neural networks (ANN) and genetic algorithms (GA) coupled by 3D Navier-Stokes flow solver has been used to improve the performance of an initial geometry of a Francis runner. The results show the good ability of optimization algorithm and the final geometry has better efficiency with initial geometry. The goal was to optimize the geometry of the blades of GAMM turbine runner which leads to maximum total efficiency by changing the design parameters of camber line in at least 5 sections of a blade. The efficiency of the optimized geometry is improved from 90.7% to 92.5%. Finally, design parameters and the way of selection have been considered and discussed.

Keywords: Francis Turbine, Runner, Optimization, CFD

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Authors: A. Ghaffari, A. Meghdari, D. Naderi, S. Eslami

Abstract:

In this paper an algorithm based on the adaptive neuro-fuzzy controller is provided to enhance the tipover stability of mobile manipulators when they are subjected to predefined trajectories for the end-effector and the vehicle. The controller creates proper configurations for the manipulator to prevent the robot from being overturned. The optimal configuration and thus the most favorable control are obtained through soft computing approaches including a combination of genetic algorithm, neural networks, and fuzzy logic. The proposed algorithm, in this paper, is that a look-up table is designed by employing the obtained values from the genetic algorithm in order to minimize the performance index and by using this data base, rule bases are designed for the ANFIS controller and will be exerted on the actuators to enhance the tipover stability of the mobile manipulator. A numerical example is presented to demonstrate the effectiveness of the proposed algorithm.

Keywords: Mobile Manipulator, Tipover Stability Enhancement, Adaptive Neuro-Fuzzy Inference Controller System, Soft Computing.

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Authors: R. Tur, A. Yardımcı

Abstract:

Imperfect knowledge cannot be avoided all the time. Imperfections may have several forms; uncertainties, imprecision and incompleteness. When we look to classification of methods for the management of imperfect knowledge we see fuzzy set-based techniques. The choice of a method to process data is linked to the choice of knowledge representation, which can be numerical, symbolic, logical or semantic and it depends on the nature of the problem to be solved for example decision support, which will be mentioned in our study. Fuzzy Logic is used for its ability to manage imprecise knowledge, but it can take advantage of the ability of neural networks to learn coefficients or functions. Such an association of methods is typical of so-called soft computing. In this study a new method was used for the management of imprecision for collected knowledge which related to economic analysis of construction industry in Turkey. Because of sudden changes occurring in economic factors decrease competition strength of construction companies. The better evaluation of these changes in economical factors in view of construction industry will made positive influence on company-s decisions which are dealing construction.

Keywords: Fuzzy logic, decision support systems, construction industry.

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Authors: G. Türkmen, Ö. Tekin, K. Kurtuluş, Y. Y. Yurtseven, M. Baran

Abstract:

A scanning electron microscope (SEM) is a type of electron microscope mainly used in nanoscience and nanotechnology areas. Automatic image recognition and classification are among the general areas of application concerning SEM. In line with these usages, the present paper proposes a deep learning algorithm that classifies SEM images into nine categories by means of an online application to simplify the process. The NFFA-EUROPE - 100% SEM data set, containing approximately 21,000 images, was used to train and test the algorithm at 80% and 20%, respectively. Validation was carried out using a separate data set obtained from the Middle East Technical University (METU) in Turkey. To increase the accuracy in the results, the Inception ResNet-V2 model was used in view of the Fine-Tuning approach. By using a confusion matrix, it was observed that the coated-surface category has a negative effect on the accuracy of the results since it contains other categories in the data set, thereby confusing the model when detecting category-specific patterns. For this reason, the coated-surface category was removed from the train data set, hence increasing accuracy by up to 96.5%.

Keywords: Convolutional Neural Networks, deep learning, image classification, scanning electron microscope.

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Authors: Neil Bar, Andrew Heweston

Abstract:

Probability of failure (PF) often appears alongside factor of safety (FS) in design acceptance criteria for rock slope, underground excavation and open pit mine designs. However, the design acceptance criteria generally provide no guidance relating to how PF should be calculated for homogeneous and heterogeneous rock masses, or what qualifies a ‘reasonable’ PF assessment for a given slope design. Observational and kinematic methods were widely used in the 1990s until advances in computing permitted the routine use of numerical modelling. In the 2000s and early 2010s, PF in numerical models was generally calculated using the point estimate method. More recently, some limit equilibrium analysis software offer statistical parameter inputs along with Monte-Carlo or Latin-Hypercube sampling methods to automatically calculate PF. Factors including rock type and density, weathering and alteration, intact rock strength, rock mass quality and shear strength, the location and orientation of geologic structure, shear strength of geologic structure and groundwater pore pressure influence the stability of rock slopes. Significant engineering and geological judgment, interpretation and data interpolation is usually applied in determining these factors and amalgamating them into a geotechnical model which can then be analysed. Most factors are estimated ‘approximately’ or with allowances for some variability rather than ‘exactly’. When it comes to numerical modelling, some of these factors are then treated deterministically (i.e. as exact values), while others have probabilistic inputs based on the user’s discretion and understanding of the problem being analysed. This paper discusses the importance of understanding the key aspects of slope design for homogeneous and heterogeneous rock masses and how they can be translated into reasonable PF assessments where the data permits. A case study from a large open pit gold mine in a complex geological setting in Western Australia is presented to illustrate how PF can be calculated using different methods and obtain markedly different results. Ultimately sound engineering judgement and logic is often required to decipher the true meaning and significance (if any) of some PF results.

Keywords: Probability of failure, point estimate method, Monte-Carlo simulations, sensitivity analysis, slope stability.

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Authors: Eduardo Sant'Ana da Silva, Andre Luiz Pires Guedes, Eduardo Todt

Abstract:

Independent spanning trees (ISTs) provide a number of advantages in data broadcasting. One can cite the use in fault tolerance network protocols for distributed computing and bandwidth. However, the problem of constructing multiple ISTs is considered hard for arbitrary graphs. In this paper we present an efficient algorithm to construct ISTs on hypercubes that requires minimum resources to be performed.

Keywords: Hypercube, Independent Spanning Trees, Networks On Chip, Systems On Chip.

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Authors: Iuliia Zarubiieva, Joyun Tseng, Vishwesh Kulkarni

Abstract:

Recent researches has focused on nucleic acids as a substrate for designing biomolecular circuits for in situ monitoring and control. A common approach is to express them by a set of idealised abstract chemical reaction networks (ACRNs). Here, we present new results on how abstract chemical reactions, viz., catalysis, annihilation and degradation, can be used to implement circuit that accurately computes logarithm function using the method of Arithmetic-Geometric Mean (AGM), which has not been previously used in conjunction with ACRNs.

Keywords: Abstract chemical reaction network, DNA strand displacement, natural logarithm.

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Authors: V. K. Banga

Abstract:

Robots are now playing a very promising role in industries. Robots are commonly used in applications in repeated operations or where operation by human is either risky or not feasible. In most of the industrial applications, robotic arm manipulators are widely used. Robotic arm manipulator with two link or three link structures is commonly used due to their low degrees-of-freedom (DOF) movement. As the DOF of robotic arm increased, complexity increases. Instrumentation involved with robotics plays very important role in order to interact with outer environment. In this work, optimal control for movement of various DOFs of robotic arm using various soft computing techniques has been presented. We have discussed about different robotic structures having various DOF robotics arm movement. Further stress is on kinematics of the arm structures i.e. forward kinematics and inverse kinematics. Trajectory planning of robotic arms using soft computing techniques is demonstrating the flexibility of this technique. The performance is optimized for all possible input values and results in optimized movement as resultant output. In conclusion, soft computing has been playing very important role for achieving optimized movement of robotic arm. It also requires very limited knowledge of the system to implement soft computing techniques.

Keywords: Artificial intelligence, kinematics, robotic arm, neural networks, fuzzy logic.

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Authors: Farhad Asadi, Mohammad Javad Mollakazemi, Aref Ghafouri

Abstract:

Recent research in neural networks science and neuroscience for modeling complex time series data and statistical learning has focused mostly on learning from high input space and signals. Local linear models are a strong choice for modeling local nonlinearity in data series. Locally weighted projection regression is a flexible and powerful algorithm for nonlinear approximation in high dimensional signal spaces. In this paper, different learning scenario of one and two dimensional data series with different distributions are investigated for simulation and further noise is inputted to data distribution for making different disordered distribution in time series data and for evaluation of algorithm in locality prediction of nonlinearity. Then, the performance of this algorithm is simulated and also when the distribution of data is high or when the number of data is less the sensitivity of this approach to data distribution and influence of important parameter of local validity in this algorithm with different data distribution is explained.

Keywords: Local nonlinear estimation, LWPR algorithm, Online training method.

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Authors: Tingke Wu, Man Yuan

Abstract:

“National Territorial Planning (2016-2030)” was issued by the State Council of China in 2017. As an important initiative of putting it into effect, territorial planning at provincial level makes overall arrangement of territorial development, resources and environment protection, comprehensive renovation and security system construction. Hubei province, as the pivot of the “Rise of Central China” national strategy, is now confronted with great opportunities and challenges in territorial development, protection, and renovation. Territorial spatial pattern experiences long time evolution, influenced by multiple internal and external driving forces. It is not clear what are the main causes of its formation and what are effective ways of optimizing it. By analyzing land use data in 2016, this paper reveals present status of territory in Hubei. Combined with economic and social data and construction information, driving forces of territorial spatial pattern are then analyzed. Research demonstrates that the three types of territorial space aggregate distinctively. The four aspects of driving forces include natural background which sets the stage for main functions, population and economic factors which generate agglomeration effect, transportation infrastructure construction which leads to axial expansion and significant provincial strategies which encourage the established path. On this basis, targeted strategies for optimizing territory spatial pattern are then put forward. Hierarchical protection pattern should be established based on development intensity control as respect for nature. By optimizing the layout of population and industry and improving the transportation network, polycentric network-based development pattern could be established. These findings provide basis for Hubei Territorial Planning, and reference for future territorial planning in other provinces.

Keywords: Driving forces, Hubei, optimizing strategies, spatial pattern, territory.

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Authors: R. M. López-Gutiérrez, L. Cardoza-Avendaño, H. Cervantes-De Ávila, J. A. Michel-Macarty, C. Cruz-Hernández, A. Arellano-Delgado, R. Carmona-Rodríguez

Abstract:

In this paper, synchronization of multiple chaotic semiconductor lasers is achieved by appealing to complex system theory. In particular, we consider dynamical networks composed by semiconductor laser, as interconnected nodes, where the interaction in the networks are defined by coupling the first state of each node. An interest case is synchronized with master-slave configuration in star topology. Nodes of these networks are modeled for the laser and simulate by Matlab. These results are applicable to private communication.

Keywords: Synchronization, chaotic laser, network.

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Authors: Sana Testouri, Karim Saadaoui, Mohamed Benrejeb

Abstract:

This paper presents a Particle Swarm Optimization (PSO) method for determining the optimal parameters of a first-order controller for TCP/AQM system. The model TCP/AQM is described by a second-order system with time delay. First, the analytical approach, based on the D-decomposition method and Lemma of Kharitonov, is used to determine the stabilizing regions of a firstorder controller. Second, the optimal parameters of the controller are obtained by the PSO algorithm. Finally, the proposed method is implemented in the Network Simulator NS-2 and compared with the PI controller.

Keywords: AQM, first-order controller, time delay, stability, PSO.

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Authors: Maria de Nazaré Moraes Soares, Silvia Maria Dias Pedro Rebouças, José Carlos Lázaro

Abstract:

The Solidarity Economy (SE) acts in the re-articulation of the economic field to the other spheres of social action. The significant participation of women in SE resulted in the formation of a national network of self-managed enterprises in Brazil: The Solidarity and Feminist Economy Network (SFEN). The objective of the research is to identify factors of gender justice and feminist self-management practices that adhere to the reality of women in SE enterprises. The conceptual apparatus related to feminist studies in this research covers Nancy Fraser approaches on gender justice, and Patricia Yancey Martin approaches on feminist management practices, and authors of postcolonial feminism such as Mohanty and Maria Lugones, who lead the discussion to peripheral contexts, a necessary perspective when observing the women’s movement in SE. The research has a quantitative nature in the phases of data collection and analysis. The data collection was performed through two data sources: the database mapped in Brazil in 2010-2013 by the National Information System in Solidary Economy and 150 questionnaires with women from 16 enterprises in SFEN, in a state of Brazilian northeast. The data were analyzed using the multivariate statistical technique of Factor Analysis. The results show that the factors that define gender justice and feminist self-management practices in SE are interrelated in several levels, proving statistically the intersectional condition of the issue of women. The evidence from the quantitative analysis allowed us to understand the dimensions of gender justice and feminist management practices intersectionality; in this sense, the non-distribution of domestic work interferes in non-representation of women in public spaces, especially in peripheral contexts. The study contributes with important reflections to the studies of this area and can be complemented in the future with a qualitative research that approaches the perspective of women in the context of the SE self-management paradigm.

Keywords: Feminist management practices, gender justice, self-management, solidarity economy.

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Authors: Shuguo Yang, Xiaoyan Yang

Abstract:

It is practically significant to research the traffic flow of intersection because the capacity of intersection affects the efficiency of highway network directly. This paper analyzes the traffic conditions of an intersection in certain urban by the methods of queuing theory and statistical experiment, sets up a corresponding mathematical model and compares it with the actual values. The result shows that queuing theory is applied in the study of intersection traffic flow and it can provide references for the other similar designs.

Keywords: Intersection, Queuing theory, Statistical experiment, System metrics.

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Authors: Chia-Hung Lin, Mei-Sung Kang, Cong-Hui Huang, Chao-Lin Kuo

Abstract:

This paper proposes fractal patterns for power quality (PQ) detection using color relational analysis (CRA) based classifier. Iterated function system (IFS) uses the non-linear interpolation in the map and uses similarity maps to construct various fractal patterns of power quality disturbances, including harmonics, voltage sag, voltage swell, voltage sag involving harmonics, voltage swell involving harmonics, and voltage interruption. The non-linear interpolation functions (NIFs) with fractal dimension (FD) make fractal patterns more distinguishing between normal and abnormal voltage signals. The classifier based on CRA discriminates the disturbance events in a power system. Compared with the wavelet neural networks, the test results will show accurate discrimination, good robustness, and faster processing time for detecting disturbing events.

Keywords: Power Quality (PQ), Color Relational Analysis(CRA), Iterated Function System (IFS), Non-linear InterpolationFunction (NIF), Fractal Dimension (FD).

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