31,415 research outputs found
Penghasilan manual rjngkas penggunaan alat Total Station Sokkia Set5f dan Perisian Sdr Mapping & Design untuk automasi ukur topografi
Projek ini dilaksanakan untuk menghasilkan manual ringkas penggunaan alat Total Station Sokkia SET5F dan Perisian SDR Mapping & Design dalam menghasilkan pelan topografi yang lengkap mengikut konsep field to finish. Manual telah dihasilkan dalam dua bentuk iaitu buku dan CD-ROM. Manual ini telah dinilai berdasarkan data yang diperolehi daripada 7 orang responden melalui kaedah Borang Penilaian Manual. Analisis data dilakukan menggunakan perisian SPSS versi 11.0. Hasil analisis skor min menunjukkan kesemua responden bersetuju bahawa manual dalam bentuk buku ini menarik Min ( M ) ^ ^ dan Sisihan Piawai (SD) = .535 tetapi kurang interaktif (M) = 2.29 dan (SD) = 0.488. Berbanding dengan manual dalam format CD-ROM yang mencatat nilai (M) = 3.57 dan (SD) = 0.535 semua responden bersetuju bahawa manual ini mesra pengguna dan lebih interakti
An Interactive Fuzzy Satisficing Method for Fuzzy Random Multiobjective 0-1 Programming Problems through Probability Maximization Using Possibility
In this paper, we focus on multiobjective 0-1 programming problems under the situation where stochastic uncertainty and vagueness exist at the same time. We formulate them as
fuzzy random multiobjective 0-1 programming problems where coefficients of objective functions are fuzzy random variables. For the formulated problem, we propose an interactive fuzzy satisficing method through probability maximization using of possibility
A STOCHASTIC SIMULATION-BASED HYBRID INTERVAL FUZZY PROGRAMMING APPROACH FOR OPTIMIZING THE TREATMENT OF RECOVERED OILY WATER
In this paper, a stochastic simulation-based hybrid interval fuzzy programming (SHIFP) approach
is developed to aid the decision-making process by solving fuzzy linear optimization problems.
Fuzzy set theory, probability theory, and interval analysis are integrated to take into account the
effect of imprecise information, subjective judgment, and variable environmental conditions. A
case study related to oily water treatment during offshore oil spill clean-up operations is conducted
to demonstrate the applicability of the proposed approach. The results suggest that producing a
random sequence of triangular fuzzy numbers in a given interval is equivalent to a normal
distribution when using the centroid defuzzification method. It also shows that the defuzzified
optimal solutions follow the normal distribution and range from 3,000-3,700 tons, given the
budget constraint (CAD 110,000-150,000). The normality seems to be able to propagate
throughout the optimization process, yet this interesting finding deserves more in-depth study
and needs more rigorous mathematical proof to validate its applicability and feasibility. In
addition, the optimal decision variables can be categorized into several groups with different
probability such that decision makers can wisely allocate limited resources with higher
confidence in a short period of time. This study is expected to advise the industries and
authorities on how to distribute resources and maximize the treatment efficiency of oily
water in a short period of time, particularly in the context of harsh environments
Solving P - Norm Intuitionistic Fuzzy Programming Problem
In this paper, notion of p - norm generalized trapezoidal intuitionistic
fuzzy numbers is introduced. A new ranking method is introduced for p - norm
generalized trapezoidal intuitionistic fuzzy numbers. Also we consider linear
programming problem in intuitionistic fuzzy environment. In this problem, all
the coefficients and variables are represented by p - norm generalized
trapezoidal intuitionistic fuzzy numbers. To overcome the limitations of the
existing methods, a new method is proposed to compute the intuitionistic fuzzy
optimal solution for intuitionistic fuzzy linear programming problem. An
illustrative numerical example is solved to demonstrate the efficiency of the
proposed approach.Comment: some erro
Automatic programming methodologies for electronic hardware fault monitoring
This paper presents three variants of Genetic Programming (GP) approaches for intelligent online performance monitoring of electronic circuits and systems. Reliability modeling of electronic circuits can be best performed by the Stressor - susceptibility interaction model. A circuit or a system is considered to be failed once the stressor has exceeded the susceptibility limits. For on-line prediction, validated stressor vectors may be obtained by direct measurements or sensors, which after pre-processing and standardization are fed into the GP models. Empirical results are compared with artificial neural networks trained using backpropagation algorithm and classification and regression trees. The performance of the proposed method is evaluated by comparing the experiment results with the actual failure model values. The developed model reveals that GP could play an important role for future fault monitoring systems.This research was supported by the International Joint Research Grant of the IITA (Institute of Information Technology Assessment) foreign professor invitation program of the MIC (Ministry of Information and Communication), Korea
Strict Solution Method for Linear Programming Problem with Ellipsoidal Distributions under Fuzziness
This paper considers a linear programming problem with ellipsoidal distributions including fuzziness. Since this problem is not well-defined due to randomness and fuzziness, it is hard to solve it directly. Therefore, introducing chance constraints, fuzzy goals and possibility measures, the proposed model is transformed into the deterministic equivalent problems. Furthermore, since it is difficult to solve the main problem analytically and efficiently due to nonlinear programming, the solution method is constructed introducing an appropriate parameter and performing the equivalent transformations
Applications of fuzzy theories to multi-objective system optimization
Most of the computer aided design techniques developed so far deal with the optimization of a single objective function over the feasible design space. However, there often exist several engineering design problems which require a simultaneous consideration of several objective functions. This work presents several techniques of multiobjective optimization. In addition, a new formulation, based on fuzzy theories, is also introduced for the solution of multiobjective system optimization problems. The fuzzy formulation is useful in dealing with systems which are described imprecisely using fuzzy terms such as, 'sufficiently large', 'very strong', or 'satisfactory'. The proposed theory translates the imprecise linguistic statements and multiple objectives into equivalent crisp mathematical statements using fuzzy logic. The effectiveness of all the methodologies and theories presented is illustrated by formulating and solving two different engineering design problems. The first one involves the flight trajectory optimization and the main rotor design of helicopters. The second one is concerned with the integrated kinematic-dynamic synthesis of planar mechanisms. The use and effectiveness of nonlinear membership functions in fuzzy formulation is also demonstrated. The numerical results indicate that the fuzzy formulation could yield results which are qualitatively different from those provided by the crisp formulation. It is felt that the fuzzy formulation will handle real life design problems on a more rational basis
- âŠ