2,901 research outputs found
Development of accident prediction model by using artificial neural network (ANN)
Statistical or crash prediction model have frequently been used in highway
safety studies. They can be used in identify major contributing factors or establish
relationship between crashes and explanatory accident variables. The
measurements to prevent accident are from the speed reduction, widening the
roads, speed enforcement, or construct the road divider, or other else. Therefore,
the purpose of this study is to develop an accident prediction model at federal road
FT 050 Batu Pahat to Kluang. The study process involves the identification of
accident blackspot locations, establishment of general patterns of accident, analysis
of the factors involved, site studies, and development of accident prediction model
using Artificial Neural Network (ANN) applied software which named
NeuroShell2. The significant of the variables that are selected from these accident
factors are checked to ensure the developed model can give a good prediction
results. The performance of neural network is evaluated by using the Mean
Absolute Percentage Error (MAPE). The study result showed that the best neural
network for accident prediction model at federal road FT 050 is 4-10-1 with 0.1
learning rate and 0.2 momentum rate. This network model contains the lowest
value of MAPE and highest value of linear correlation, r which is 0.8986. This
study has established the accident point weightage as the rank of the blackspot
section by kilometer along the FT 050 road (km 1 â km 103). Several main
accident factors also have been determined along this road, and after all the data
gained, it has successfully analyzed by using artificial neural network
Pembangunan dan penilaian modul berbantukan komputer bagi subjek pemasaran : Politeknik Port Dickson
Kajian ini bertujuan membangunkan Modul Berbantukan Komputer (MBK) bagi
subjek Pemasaran. MBK ini dibangunkan dengan menggunakan pensian AutoPlay
Media dan Flash MX. Sampel kajian ini terdiri daripada 30 orang pelajar Diploma
Pemasaran di Politeknik Port Dickson. Data dikumpulkan melalui kaedah soal
selidik dan dianalisis berdasarkan kekerpan, peratusan dan skor min dengan
menggunakan perisian Statistical Package For Social Sciene (SPSS) versi 11.0.
Dapatan kajian menunjukkan penilaian terhadap pembagunan MBK di dalam proses
P&P adalah tinggi. Ini bermakna MBK ini sesuai digunakan di Politeknik Port
Dickson di dalam proses P&P
A FUZZY DECISION MAKING APPROACH IN EVALUATING FERRY SERVICE QUALITY
The service quality evaluation is undeniably important especially in highly competitive service related industry. However, service quality evaluation is not always straightforward as criteria in evaluation and customer perceptions toward services are intangible measures. This paper presents a fuzzy multi-criteria decision making approach for evaluating the service quality of ferry that transport customers between the mainland of Peninsular Malaysia and a tourist spot island. Service quality is a composite of various criteria, among them many criteria are intangible and difficult to measure. Fuzzy numbers and linguistic level based on fuzzy sets theory as a method to overcome vaguely judgment in evaluation. The crisp survey results were collected via a ten-service criteria questionnaire from eighty seven customers and computed using Best non-Fuzzy Performance and Degree of Similarity. Based on the concept of the defuzzification, the ranking of service performance is obtained. Degree of Similarity provides the level of satisfaction and its degrees for each criterion. The criterion of âservice efficiency of ferry personnelâ was the first in the ranking. All the criteria received âgoodâ and âvery goodâ for the level of satisfaction. These evaluation results facilitate the ferry operator to upgrade its ferry services and eventually meet its customersâ needs.Service quality, fuzzy number, satisfaction level, defuzzification.
Neuro-fuzzy knowledge processing in intelligent learning environments for improved student diagnosis
In this paper, a neural network implementation for a fuzzy logic-based model of the diagnostic process is proposed as a means to achieve accurate student diagnosis and updates of the student model in Intelligent Learning Environments. The neuro-fuzzy synergy allows the diagnostic model to some extent "imitate" teachers in diagnosing students' characteristics, and equips the intelligent learning environment with reasoning capabilities that can be further used to drive pedagogical decisions depending on the student learning style. The neuro-fuzzy implementation helps to encode both structured and non-structured teachers' knowledge: when teachers' reasoning is available and well defined, it can be encoded in the form of fuzzy rules; when teachers' reasoning is not well defined but is available through practical examples illustrating their experience, then the networks can be trained to represent this experience. The proposed approach has been tested in diagnosing aspects of student's learning style in a discovery-learning environment that aims to help students to construct the concepts of vectors in physics and mathematics. The diagnosis outcomes of the model have been compared against the recommendations of a group of five experienced teachers, and the results produced by two alternative soft computing methods. The results of our pilot study show that the neuro-fuzzy model successfully manages the inherent uncertainty of the diagnostic process; especially for marginal cases, i.e. where it is very difficult, even for human tutors, to diagnose and accurately evaluate students by directly synthesizing subjective and, some times, conflicting judgments
The relevance of outsourcing and leagile strategies in performance optimization of an integrated process planning and scheduling
Over the past few years growing global competition has forced the manufacturing industries to upgrade their old production strategies with the modern day approaches. As a result, recent interest has been developed towards finding an appropriate policy that could enable them to compete with others, and facilitate them to emerge as a market winner. Keeping in mind the abovementioned facts, in this paper the authors have proposed an integrated process planning and scheduling model inheriting the salient features of outsourcing, and leagile principles to compete in the existing market scenario. The paper also proposes a model based on leagile principles, where the integrated planning management has been practiced. In the present work a scheduling problem has been considered and overall minimization of makespan has been aimed. The paper shows the relevance of both the strategies in performance enhancement of the industries, in terms of their reduced makespan. The authors have also proposed a new hybrid Enhanced Swift Converging Simulated Annealing (ESCSA) algorithm, to solve the complex real-time scheduling problems. The proposed algorithm inherits the prominent features of the Genetic Algorithm (GA), Simulated Annealing (SA), and the Fuzzy Logic Controller (FLC). The ESCSA algorithm reduces the makespan significantly in less computational time and number of iterations. The efficacy of the proposed algorithm has been shown by comparing the results with GA, SA, Tabu, and hybrid Tabu-SA optimization methods
Applying fuzzy theory concepts to the analysis of employment diversification of farm households: methodological considerations
The Deliverable 7.2 (D7.2) of the SCARLED project provides methodological considerations for applying fuzzy set theory to the analysis of employment diversification of farm households. It presents a Mamdani's type fuzzy inference model and describes its application within the project's framework. The model consists of ten variables that are grouped into the four factors: (i) necessity to diversify, (ii) internal preconditions, (iii) external preconditions, and (iv) attitudes. The coherence of these four factors with the integrated framework for the analysis of nonfarm rural employment is discussed. The model will be realised in the Fuzzy Logic Toolbox from MATLABÂź. Forty four membership functions and 138 rules are going to be implemented, tested, and adapted with survey data from the five countries: Bulgaria, Hungary, Poland, Romania, and Slovenia. The final model will be used to assess the diversification potential of 15 regions in these countries. --
Performance Evaluation of Road Traffic Control Using a Fuzzy Cellular Model
In this paper a method is proposed for performance evaluation of road traffic
control systems. The method is designed to be implemented in an on-line
simulation environment, which enables optimisation of adaptive traffic control
strategies. Performance measures are computed using a fuzzy cellular traffic
model, formulated as a hybrid system combining cellular automata and fuzzy
calculus. Experimental results show that the introduced method allows the
performance to be evaluated using imprecise traffic measurements. Moreover, the
fuzzy definitions of performance measures are convenient for uncertainty
determination in traffic control decisions.Comment: The final publication is available at http://www.springerlink.co
Fuzzy Spatial Analysis Techniques in a Business GIS Environment
The purpose of the paper is to explore the use of fuzzy logic technology in spatial analysis. Focus is laid on illustrating the value added within the context of Business GIS. We consider the issue of geomarketing for illustrative purposes. Geomarketing may be characterised as address focused marketing. The objective of the case study is to identify spatial customer potentials for a specific product, using real world customer data of an Austrian firm. Fuzzy logic is used to generate customer profiles and to model the spatial customer potential of the product in question. We will illustrate the use of fuzzy logic in comparison to crisp classification techniques and modelling with crisp operators for solving the problem and more generally how the use of fuzzy logic may be to the advantage of businesses. Univ.-Prof. Dr. Manfred M. Fischer (Department of Economic Geography and Geoinformatics, Vienna University of Economics and Business Administration) invited me to attend his special session.
- âŠ