Search results for: Fuzzy C-means clustering based attribute weighting

Authors: A. Puras Trueba, J. R. Llata García

Abstract:

A nonlinear optimal controller with a fuzzy gain scheduler has been designed and applied to a Line-Of-Sight (LOS) stabilization system. Use of Linear Quadratic Regulator (LQR) theory is an optimal and simple manner of solving many control engineering problems. However, this method cannot be utilized directly for multigimbal LOS systems since they are nonlinear in nature. To adapt LQ controllers to nonlinear systems at least a linearization of the model plant is required. When the linearized model is only valid within the vicinity of an operating point a gain scheduler is required. Therefore, a Takagi-Sugeno Fuzzy Inference System gain scheduler has been implemented, which keeps the asymptotic stability performance provided by the optimal feedback gain approach. The simulation results illustrate that the proposed controller is capable of overcoming disturbances and maintaining a satisfactory tracking performance.

Keywords: Fuzzy Gain-Scheduling, Gimbal, Line-Of-SightStabilization, LQR, Optimal Control

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2322

Authors: C. Senanayake, S. Veera Ragavan

Abstract:

Warehousing is commonly used in factories for the storage of products until delivery of orders. As the amount of products stored increases it becomes tedious to be carried out manually. In recent years, the manual storing has converted into fully or partially computer controlled systems, also known as Automated Storage and Retrieval Systems (AS/RS). This paper discusses an ASRS system, which was designed such that the best storage location for the products is determined by utilizing a fuzzy control system. The design maintains the records of the products to be/already in store and the storage/retrieval times along with the availability status of the storage locations. This paper discusses on the maintenance of the above mentioned records and the utilization of the concept of fuzzy logic in order to determine the optimum storage location for the products. The paper will further discuss on the dynamic splitting and merging of the storage locations depending on the product sizes.

Keywords: ASRS, fuzzy control systems, MySQL database, dynamic splitting and merging.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2139

Authors: Reza Ghasemi, Negin Amiri Hazaveh

Abstract:

In this paper, control methodology based on the selection of the type of traffic light and the period of the green phase to accomplish an optimum balance at intersections is proposed. This balance should be flexible to the static behavior of time, and randomness in a traffic situation; the goal of the proposed method is to reduce traffic volume in transportation, the average delay for each vehicle, and control over the crash of cars. The proposed method was specifically investigated at the intersection through an appropriate timing of traffic lights by sampling a multi-agent system. It consists of a large number of intersections, each of which is considered as an independent agent that exchanges information with each other, and the stability of each agent is provided separately. The robustness against uncertainties, scalability, and stability of the closed-loop overall system are the main merits of the proposed methodology. The simulation results show that the fuzzy intelligent controller in this multi-factor system which is a Takagi-Sugeno (TS) fuzzy is more useful than scheduling in the fixed-time method and it reduces the lengths of vehicles queuing.

Keywords: Fuzzy intelligent controller, traffic-light control, multi-agent systems, state space equations, stability.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 538

Authors: Fajaruddin Mustakim, Motohiro Fujita

Abstract:

This paper present the study carried out of accident analysis, black spot study and to develop accident predictive models based on the data collected at rural roadway, Federal Route 50 (F050) Malaysia. The road accident trends and black spot ranking were established on the F050. The development of the accident prediction model will concentrate in Parit Raja area from KM 19 to KM 23. Multiple non-linear regression method was used to relate the discrete accident data with the road and traffic flow explanatory variable. The dependent variable was modeled as the number of crashes namely accident point weighting, however accident point weighting have rarely been account in the road accident prediction Models. The result show that, the existing number of major access points, without traffic light, rise in speed, increasing number of Annual Average Daily Traffic (AADT), growing number of motorcycle and motorcar and reducing the time gap are the potential contributors of increment accident rates on multiple rural roadway.

Keywords: Accident Trends, Black Spot Study, Accident Prediction Model

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3276

Authors: P. R. Jayathilaka, K.L. Jayaratne, H.L. Premaratne

Abstract:

This research presented in this paper is an on-going project of an application of neural network and fuzzy models to evaluate the sociological factors which affect the educational performance of the students in Sri Lanka. One of its major goals is to prepare the grounds to device a counseling tool which helps these students for a better performance at their examinations, especially at their G.C.E O/L (General Certificate of Education-Ordinary Level) examination. Closely related sociological factors are collected as raw data and the noise of these data are filtered through the fuzzy interface and the supervised neural network is being utilized to recognize the performance patterns against the chosen social factors.

Keywords: Education, Fuzzy, neural network, prediction, Sociology

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1635

Authors: Pejman Hosseinioun, Hasan Shakeri, Ghasem Ghorbanirostam

Abstract:

In recent years, we have seen an increasing importance of research and study on knowledge source, decision support systems, data mining and procedure of knowledge discovery in data bases and it is considered that each of these aspects affects the others. In this article, we have merged information source and knowledge source to suggest a knowledge based system within limits of management based on storing and restoring of knowledge to manage information and improve decision making and resources. In this article, we have used method of data mining and Apriori algorithm in procedure of knowledge discovery one of the problems of Apriori algorithm is that, a user should specify the minimum threshold for supporting the regularity. Imagine that a user wants to apply Apriori algorithm for a database with millions of transactions. Definitely, the user does not have necessary knowledge of all existing transactions in that database, and therefore cannot specify a suitable threshold. Our purpose in this article is to improve Apriori algorithm. To achieve our goal, we tried using fuzzy logic to put data in different clusters before applying the Apriori algorithm for existing data in the database and we also try to suggest the most suitable threshold to the user automatically.

Keywords: Decision support system, data mining, knowledge discovery, data discovery, fuzzy logic.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2126

Authors: K. M. Faraoun, A. Boukelif

Abstract:

In the present work, we propose a new technique to enhance the learning capabilities and reduce the computation intensity of a competitive learning multi-layered neural network using the K-means clustering algorithm. The proposed model use multi-layered network architecture with a back propagation learning mechanism. The K-means algorithm is first applied to the training dataset to reduce the amount of samples to be presented to the neural network, by automatically selecting an optimal set of samples. The obtained results demonstrate that the proposed technique performs exceptionally in terms of both accuracy and computation time when applied to the KDD99 dataset compared to a standard learning schema that use the full dataset.

Keywords: Neural networks, Intrusion detection, learningenhancement, K-means clustering

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 3602

Authors: Mehrdad N. Khajavi , Golamhassan Paygane, Ali Hakima

Abstract:

Vehicle which are turning or maneuvering at high speeds are susceptible to sliding and subsequently deviate from desired path. In this paper the dynamics governing the Yaw/Roll behavior of a vehicle has been simulated. Two different simulations have been used one for the real vehicle, for which a fuzzy controller is designed to increase its directional stability property. The other simulation is for a hypothetical vehicle with much higher tire cornering stiffness which is capable of developing the required lateral forces at the tire-ground patch contact to attain the desired lateral acceleration for the vehicle to follow the desired path without slippage. This simulation model is our reference model. The logic for keeping the vehicle on the desired track in the cornering or maneuvering state is to have some braking forces on the inner or outer tires based on the direction of vehicle deviation from the desired path. The inputs to our vehicle simulation model is steer angle δ and vehicle velocity V , and the outputs can be any kinematical parameters like yaw rate, yaw acceleration, side slip angle, rate of side slip angle and so on. The proposed fuzzy controller is a feed forward controller. This controller has two inputs which are steer angle δ and vehicle velocity V, and the output of the controller is the correcting moment M, which guides the vehicle back to the desired track. To develop the membership functions for the controller inputs and output and the fuzzy rules, the vehicle simulation has been run for 1000 times and the correcting moment have been determined by trial and error. Results of the vehicle simulation with fuzzy controller are very promising and show the vehicle performance is enhanced greatly over the vehicle without the controller. In fact the vehicle performance with the controller is very near the performance of the reference ideal model.

Keywords: Vehicle, Directional Stability, Fuzzy Logic Controller, ANFIS..

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1510

Authors: Peyman Shadman Heidari, Mohammad Khorasani

Abstract:

The principal purpose of this article is to present a new method based on Adaptive Neural Network Fuzzy Inference System (ANFIS) to generate additional artificial earthquake accelerograms from presented data, which are compatible with specified response spectra. The proposed method uses the learning abilities of ANFIS to develop the knowledge of the inverse mapping from response spectrum to earthquake records. In addition, wavelet packet transform is used to decompose specified earthquake records and then ANFISs are trained to relate the response spectrum of records to their wavelet packet coefficients. Finally, an interpretive example is presented which uses an ensemble of recorded accelerograms to demonstrate the effectiveness of the proposed method.

Keywords: Adaptive Neural Network Fuzzy Inference System, Wavelet Packet Transform, Response Spectrum.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2829

Authors: Jinming Ma, Tianbing Xia, Janusz R. Getta

Abstract:

This paper presents the application of fuzzy set theory to implement of mobile advertisement anti-fraud systems. Mobile anti-fraud is a method aiming to identify mobile advertisement fraudsters. One of the main problems of mobile anti-fraud is the lack of evidence to prove a user to be a fraudster. In this paper, we implement an application by using fuzzy set theory to demonstrate how to detect cheaters. The advantage of our method is that the hardship in detecting fraudsters in small data samples has been avoided. We achieved this by giving each user a suspicious degree showing how likely the user is cheating and decide whether a group of users (like all users of a certain APP) together to be fraudsters according to the average suspicious degree. This makes the process more accurate as the data of a single user is too small to be predictable.

Keywords: Mobile internet, advertisement, anti-fraud, fuzzy set theory.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 584

Authors: Jiaji Zhou, Le Liang, Long Chen

Abstract:

Geographic Profiling has successfully assisted investigations for serial crimes. Considering the multi-cluster feature of serial criminal spots, we propose a Multi-point Centrography model as a natural extension of Single-point Centrography for geographic profiling. K-means clustering is first performed on the data samples and then Single-point Centrography is adopted to derive a probability distribution on each cluster. Finally, a weighted combinations of each distribution is formed to make next-crime spot prediction. Experimental study on real cases demonstrates the effectiveness of our proposed model.

Keywords: Geographic profiling, Centrography model, K-means algorithm

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2079

Authors: Behrooz Rezaie, Zahra Rahmani Cherati, Mohammad Reza Jahed Motlagh, Mohammad Farrokhi

Abstract:

In this paper, a fuzzy controller is designed for stabilization of the Lorenz chaotic equations. A simple Mamdani inference method is used for this purpose. This method is very simple and applicable for complex chaotic systems and it can be implemented easily. The stability of close loop system is investigated by the Lyapunov stabilization criterion. A Lyapunov function is introduced and the global stability is proven. Finally, the effectiveness of this method is illustrated by simulation results and it is shown that the performance of the system is improved.

Keywords: Chaotic system, Fuzzy control, Lorenz equation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2024

Authors: A. Habibizad Navin, A. Sadighi, M. Naghian Fesharaki, M. Mirnia, M. Teshnelab, R. Keshmiri

Abstract:

This paper presents a new data oriented model of image. Then a representation of it, ADBT, is introduced. The ability of ADBT is clustering, segmentation, measuring similarity of images etc, with desired precision and corresponding speed.

Keywords: Data oriented modelling, image, clustering, segmentation, classification, ADBT and image processing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1793

Authors: Hossein Gitinavard, Mohammad Hossein Fazel Zarandi

Abstract:

In the last decades, concerns about the environmental issues lead to professional and academic efforts on green supplier selection problems. In this sake, one of the main issues in evaluating the green supplier selection problems, which could increase the uncertainty, is the preferences of the experts' judgments about the candidate green suppliers. Therefore, preparing an expert system to evaluate the problem based on the historical data and the experts' knowledge can be sensible. This study provides an expert evaluation system to assess the candidate green suppliers under selected criteria in a multi-period approach. In addition, a ranking approach under interval-valued hesitant fuzzy set (IVHFS) environment is proposed to select the most appropriate green supplier in planning horizon. In the proposed ranking approach, the IVHFS and the last aggregation approach are considered to margin the errors and to prevent data loss, respectively. Hence, a comparative analysis is provided based on an illustrative example to show the feasibility of the proposed approach.

Keywords: Green supplier selection, expert system, ranking approach, interval-valued hesitant fuzzy setting.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1417

Authors: Ahmad Aljaafreh

Abstract:

This paper proposes a hierarchical hidden Markov model (HHMM) to model the detection of M vehicles in a wireless sensor network (WSN). The HHMM model contains an extra level of hidden Markov model to model the temporal transitions of each state of the first HMM. By modeling the temporal transitions, only those hypothesis with nonzero transition probabilities needs to be tested. Thus, this method efficiently reduces the computation load, which is preferable in WSN applications.This paper integrates several techniques to optimize the detection performance. The output of the states of the first HMM is modeled as Gaussian Mixture Model (GMM), where the number of states and the number of Gaussians are experimentally determined, while the other parameters are estimated using Expectation Maximization (EM). HHMM is used to model the sequence of the local decisions which are based on multiple hypothesis testing with maximum likelihood approach. The states in the HHMM represent various combinations of vehicles of different types. Due to the statistical advantages of multisensor data fusion, we propose a heuristic based on fuzzy weighted majority voting to enhance cooperative classification of moving vehicles within a region that is monitored by a wireless sensor network. A fuzzy inference system weighs each local decision based on the signal to noise ratio of the acoustic signal for target detection and the signal to noise ratio of the radio signal for sensor communication. The spatial correlation among the observations of neighboring sensor nodes is efficiently utilized as well as the temporal correlation. Simulation results demonstrate the efficiency of this scheme.

Keywords: Classification, decision fusion, fuzzy logic, hidden Markov model

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 6243

Authors: Hossein Pazhoumand-Dar, Amir Mohsen Toliyat Abolhassani, Ehsan Saeedi

Abstract:

Speed estimation is one of the important and practical tasks in machine vision, Robotic and Mechatronic. the availability of high quality and inexpensive video cameras, and the increasing need for automated video analysis has generated a great deal of interest in machine vision algorithms. Numerous approaches for speed estimation have been proposed. So classification and survey of the proposed methods can be very useful. The goal of this paper is first to review and verify these methods. Then we will propose a novel algorithm to estimate the speed of moving object by using fuzzy concept. There is a direct relation between motion blur parameters and object speed. In our new approach we will use Radon transform to find direction of blurred image, and Fuzzy sets to estimate motion blur length. The most benefit of this algorithm is its robustness and precision in noisy images. Our method was tested on many images with different range of SNR and is satisfiable.

Keywords: Blur Analysis, Fuzzy sets, Speed estimation.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1876

Authors: V. Gomathi, Dr. K. Ramar, A. Santhiyaku Jeevakumar

Abstract:

Facial expression analysis plays a significant role for human computer interaction. Automatic analysis of human facial expression is still a challenging problem with many applications. In this paper, we propose neuro-fuzzy based automatic facial expression recognition system to recognize the human facial expressions like happy, fear, sad, angry, disgust and surprise. Initially facial image is segmented into three regions from which the uniform Local Binary Pattern (LBP) texture features distributions are extracted and represented as a histogram descriptor. The facial expressions are recognized using Multiple Adaptive Neuro Fuzzy Inference System (MANFIS). The proposed system designed and tested with JAFFE face database. The proposed model reports 94.29% of classification accuracy.

Keywords: Adaptive neuro-fuzzy inference system, Facialexpression, Local binary pattern, Uniform Histogram

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2099

Authors: Rahma Souli-Jbali, Minyar Sassi Hidri, Rahma Ben Ayed

Abstract:

Grid of computing nodes has emerged as a representative means of connecting distributed computers or resources scattered all over the world for the purpose of computing and distributed storage. Since fault tolerance becomes complex due to the availability of resources in decentralized grid environment, it can be used in connection with replication in data grids. The objective of our work is to present fault tolerance in data grids with data replication-driven model based on clustering. The performance of the protocol is evaluated with Omnet++ simulator. The computational results show the efficiency of our protocol in terms of recovery time and the number of process in rollbacks.

Keywords: Data grids, fault tolerance, chandy-lamport, clustering.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 945

Authors: F. Raja, M. Rahgozar, F. Oroumchian

Abstract:

XML is a markup language which is becoming the standard format for information representation and data exchange. A major purpose of XML is the explicit representation of the logical structure of a document. Much research has been performed to exploit logical structure of documents in information retrieval in order to precisely extract user information need from large collections of XML documents. In this paper, we describe an XML information retrieval weighting scheme that tries to find the most relevant elements in XML documents in response to a user query. We present this weighting model for information retrieval systems that utilize plausible inferences to infer the relevance of elements in XML documents. We also add to this model the Dempster-Shafer theory of evidence to express the uncertainty in plausible inferences and Dempster-Shafer rule of combination to combine evidences derived from different inferences.

Keywords: Dempster-Shafer theory, plausible inferences, XMLinformation retrieval.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1526

Authors: Payam Nabhani, Sima Radmanesh

Abstract:

Opportunistic network is a kind of Delay Tolerant Networks (DTN) where the nodes in this network come into contact with each other opportunistically and communicate wirelessly and, an end-to-end path between source and destination may have never existed, and disconnection and reconnection is common in the network. In such a network, because of the nature of opportunistic network, perhaps there is no a complete path from source to destination for most of the time and even if there is a path; the path can be very unstable and may change or break quickly. Therefore, routing is one of the main challenges in this environment and, in order to make communication possible in an opportunistic network, the intermediate nodes have to play important role in the opportunistic routing protocols. In this paper we proposed an Adaptive Fuzzy Routing in opportunistic network (AFRON). This protocol is using the simple parameters as input parameters to find the path to the destination node. Using Message Transmission Count, Message Size and Time To Live parameters as input fuzzy to increase delivery ratio and decrease the buffer consumption in the all nodes of network.

Keywords: Opportunistic Routing, Fuzzy Routing, Opportunistic Network, Message Routing.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1534

Authors: M. Zerikat, M. Bendjebbar, N. Benouzza

Abstract:

In this paper, a novel approach for robust trajectory tracking of induction motor drive is presented. By combining variable structure systems theory with fuzzy logic concept and neural network techniques, a new algorithm is developed. Fuzzy logic was used for the adaptation of the learning algorithm to improve the robustness of learning and operating of the neural network. The developed control algorithm is robust to parameter variations and external influences. It also assures precise trajectory tracking with the prescribed dynamics. The algorithm was verified by simulation and the results obtained demonstrate the effectiveness of the designed controller of induction motor drives which considered as highly non linear dynamic complex systems and variable characteristics over the operating conditions.

Keywords: Induction motor, fuzzy-logic control, neural network control, indirect field oriented control.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2455

Authors: Do Hyeung Kim, Dae Hee Seo, Byung Doo Kim, Byung Gil Lee

Abstract:

As many recent researches being implemented in aviation and maritime aspects, strong doubts have been raised concerning the reliability of the estimation of collision risk. It is shown that using position and velocity of objects can lead to imprecise results. In this paper, therefore, a new approach to the estimation of collision risks using pose and shape of objects is proposed. Simulation results are presented validating the accuracy of the new criterion to adapt to collision risk algorithm based on fuzzy logic.

Keywords: Collision risk, Pose and shape, Fuzzy logic.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1905

Authors: Sitthichon Kanitthakun, Pinit Kumhom, Kosin Chamnongthai

Abstract:

In quality control of freeze-dried durian, crispiness is a key quality index of the product. Generally, crispy testing has to be done by a destructive method. A nondestructive testing of the crispiness is required because the samples can be reused for other kinds of testing. This paper proposed a crispiness classification method of freeze-dried durians using fuzzy logic for decision making. The physical changes of a freeze-dried durian include the pores appearing in the images. Three physical features including (1) the diameters of pores, (2) the ratio of the pore area and the remaining area, and (3) the distribution of the pores are considered to contribute to the crispiness. The fuzzy logic is applied for making the decision. The experimental results comparing with food expert opinion showed that the accuracy of the proposed classification method is 83.33 percent.

Keywords: Durian, crispiness, freeze drying, pore, fuzzy logic.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1963

Authors: T. Wanyama, B. Far

Abstract:

Automatic irrigation systems usually conveniently protect landscape investment. While conventional irrigation systems are known to be inefficient, automated ones have the potential to optimize water usage. In fact, there is a new generation of irrigation systems that are smart in the sense that they monitor the weather, soil conditions, evaporation and plant water use, and automatically adjust the irrigation schedule. In this paper, we present an agent based smart irrigation system. The agents are built using a mix of commercial off the shelf software, including MATLAB, Microsoft Excel and KEPServer Ex5 OPC server, and custom written code. The Irrigation Scheduler Agent uses fuzzy logic to integrate the information that affect the irrigation schedule. In addition, the Multi-Agent system uses Open Platform Connectivity (OPC) technology to share data. OPC technology enables the Irrigation Scheduler Agent to communicate over the Internet, making the system scalable to a municipal or regional agent based water monitoring, management, and optimization system. Finally, this paper presents simulation and pilot installation test result that show the operational effectiveness of our system.

Keywords: Community water usage, fuzzy logic, irrigation, multi-agent system.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1330

Authors: Ghada Elshafei, Abdelazim Negm

Abstract:

Recently, the green architecture becomes a significant way to a sustainable future. Green building designs involve finding the balance between comfortable homebuilding and sustainable environment. Moreover, the utilization of the new technologies such as artificial intelligence techniques are used to complement current practices in creating greener structures to keep the built environment more sustainable. The most common objectives in green buildings should be designed to minimize the overall impact of the built environment that effect on ecosystems in general and in particularly human health and natural environment. This will lead to protecting occupant health, improving employee productivity, reducing pollution and sustaining the environmental. In green building design, multiple parameters which may be interrelated, contradicting, vague and of qualitative/quantitative nature are broaden to use. This paper presents a comprehensive critical state- ofart- review of current practices based on fuzzy and its combination techniques. Also, presented how green architecture/building can be improved using the technologies that been used for analysis to seek optimal green solutions strategies and models to assist in making the best possible decision out of different alternatives.

Keywords: Green architecture/building, technologies, optimization, strategies, fuzzy techniques and models.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2517

Authors: N. Subramanian, C. Murugesan

Abstract:

The double difference sequence space I2 (M, of fuzzy numbers for both 1 < p < oo and 0 < p < 1, is introduced. Some general properties of this sequence space are studied. Some inclusion relations involving this sequence space are obtained.

Keywords: Orlicz function, solid space, metric space, completeness

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1006

Authors: Besa Muslimi, Miriam A. M. Capretz, Jagath Samarabandu

Abstract:

Artificial neural networks (ANN) have the ability to model input-output relationships from processing raw data. This characteristic makes them invaluable in industry domains where such knowledge is scarce at best. In the recent decades, in order to overcome the black-box characteristic of ANNs, researchers have attempted to extract the knowledge embedded within ANNs in the form of rules that can be used in inference systems. This paper presents a new technique that is able to extract a small set of rules from a two-layer ANN. The extracted rules yield high classification accuracy when implemented within a fuzzy inference system. The technique targets industry domains that possess less complex problems for which no expert knowledge exists and for which a simpler solution is preferred to a complex one. The proposed technique is more efficient, simple, and applicable than most of the previously proposed techniques.

Keywords: fuzzy rule extraction, fuzzy systems, knowledgeacquisition, pattern recognition, artificial neural networks.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 1576

Authors: W. Phanwanich, O. Kumdee, P. Ritthipravat, Y. Wongsawat

Abstract:

In order to alleviate the mental and physical problems of persons with disabilities, animal-assisted therapy (AAT) is one of the possible modalities that employs the merit of the human-animal interaction. Nevertheless, to achieve the purpose of AAT for persons with severe disabilities (e.g. spinal cord injury, stroke, and amyotrophic lateral sclerosis), real-time animal language interpretation is desirable. Since canine behaviors can be visually notable from its tail, this paper proposes the automatic real-time interpretation of canine tail language for human-canine interaction in the case of persons with severe disabilities. Canine tail language is captured via two 3-axis accelerometers. Directions and frequencies are selected as our features of interests. The novel fuzzy rules based on Gaussian-Trapezoidal model and center of gravity (COG)-based defuzzification method are proposed in order to interpret the features into four canine emotional behaviors, i.e., agitate, happy, scare and neutral as well as its blended emotional behaviors. The emotional behavior model is performed in the simulated dog and has also been evaluated in the real dog with the perfect recognition rate.

Keywords: Animal-assisted therapy (AAT), Persons with disabilities, Canine tail language, Fuzzy emotional behavior model

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2009

Authors: Phruksaphanrat B.

Abstract:

This research proposes a preemptive fuzzy goal programming model for multi-objective multi-mode resource constrained project scheduling problem. The objectives of the problem are minimization of the total time and the total cost of the project. Objective in a multi-mode resource-constrained project scheduling problem is often a minimization of makespan. However, both time and cost should be considered at the same time with different level of important priorities. Moreover, all elements of cost functions in a project are not included in the conventional cost objective function. Incomplete total project cost causes an error in finding the project scheduling time. In this research, preemptive fuzzy goal programming is presented to solve the multi-objective multi-mode resource constrained project scheduling problem. It can find the compromise solution of the problem. Moreover, it is also flexible in adjusting to find a variety of alternative solutions. 

Keywords: Multi-mode resource constrained project scheduling problem, Fuzzy set, Goal programming, Preemptive fuzzy goal programming.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2754

Authors: B. Vahdani, R. Tavakkoli-Moghaddam, A. Baboli, S. M. Mousavi

Abstract:

Focusing on the environmental issues, including the reduction of scrap and consumer residuals, along with the benefiting from the economic value during the life cycle of goods/products leads the companies to have an important competitive approach. The aim of this paper is to present a new mixed nonlinear facility locationallocation model in recycling collection networks by considering multi-echelon, multi-suppliers, multi-collection centers and multifacilities in the recycling network. To make an appropriate decision in reality, demands, returns, capacities, costs and distances, are regarded uncertain in our model. For this purpose, a fuzzy mathematical programming-based possibilistic approach is introduced as a solution methodology from the recent literature to solve the proposed mixed-nonlinear programming model (MNLP). The computational experiments are provided to illustrate the applicability of the designed model in a supply chain environment and to help the decision makers to facilitate their analysis.

Keywords: Location-allocation model, recycling collection networks, fuzzy mathematical programming.

Procedia APA BibTeX Chicago EndNote Harvard JSON MLA RIS XML ISO 690 PDF Downloads 2093