66,766 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 β 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
Postmodern Fuzzy System Theory: A Deconstruction Approach Based on Kabbalah
Modern general system theory proposed a holistic integrative approach based on input-state-output dynamics as opposed to the traditional reductionist detail based approach. Information complexity and uncertainty required a fuzzy system theory, based on fuzzy sets and fuzzy logic. While successful in dealing with analysis, synthesis and control of technical engineering systems, general system theory and fuzzy system theory could not fully deal with humanistic and human-like intelligent systems which combine technical engineering components with human or human-like components characterized by their cognitive, emotional/motivational and behavioral/action levels of operation. Such humanistic systems are essential in artificial intelligence, cognitive and behavioral science applications, organization management and social systems, man-machine systems or human factor systems, behavioral knowledge based economics and finance applications. We are introducing here a βpostmodern fuzzy system theoryβ for controlled state dynamics and output fuzzy systems and fuzzy rule based systems using our earlier postmodern fuzzy set theory and a Kabbalah possible worlds model of modal logic and semantics type. In order to create a postmodern fuzzy system theory, we βdeconstructβ a fuzzy system in order to incorporate in it the cognitive, emotional and behavioral actions and expressions levels characteristic for humanistic systems. Kabbalah offers a structural, fractal and hierarchic model for integrating cognition, emotions and behavior. We obtain a canonic deconstruction for a fuzzy system into its cognitive, emotional and behavioral fuzzy subsystems
ΠΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΎΠ½Π½Π°Ρ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠ° Π°Π½Π°Π»ΠΈΠ·Π° Π½Π°Π²ΡΠΊΠΎΠ² ΠΈ ΡΠΌΠ΅Π½ΠΈΠΉ ΠΊΠΎΠ½ΡΠΈΠ½Π³Π΅Π½ΡΠ° ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² Π²ΡΡΡΠ΅Π³ΠΎ ΡΡΠ΅Π±Π½ΠΎΠ³ΠΎ Π·Π°Π²Π΅Π΄Π΅Π½ΠΈΡ
In the below article, the application of the fuzzy logical conclusion method is considered as decision-maker in the process of analyzing the students skills and abilities based on the requirements of potential employers, in order to reduce the time of the first interview for potential candidates on a vacant position. When analyzing the results of the assessment of the competence of university students, a certain degree of fuzziness arises. In modern practice, fuzzy logic is used in many different assessment methods, including questioning, interviewing, testing, descriptive method, classification method, pairwise comparison, rating method, business games competence models, and the like. Each of the methods has its advantages and disadvantages, but they are effective only as part of a unified personnel management system. As a method for implementing a systematic approach to the assessment of the contingent of students, it is proposed to use fuzzy logic, a mathematical apparatus that allows you to build a model of an object based on fuzzy judgments. The use of fuzzy logic, the mathematical apparatus of which allows you to build a model of the object, based on fuzzy reasoning and rules. The most important condition for creating such a model is to translate the fuzzy, qualitative assessments used by man into the language of mathematics, which will be understood by the computer. The most used are fuzzy inferences using the Mamdani and Sugeno methods. In a fuzzy inference of the Mamdani type, the value of the output variable is given by fuzzy terms, in the conclusion of the Sugeno type, as a linear combination of the input variables. Research in the field of application of fuzzy logic in socio-economic systems suggests that it can be used to assess the competencies of university students.Π Π΄Π°Π½Π½ΠΎΠΉ ΡΠ°Π±ΠΎΡΠ΅ ΡΠ°ΡΡΠΌΠΎΡΡΠ΅Π½ΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ ΠΌΠ΅ΡΠΎΠ΄Π° Π½Π΅ΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π»ΠΎΠ³ΠΈΡΠ΅ΡΠΊΠΎΠ³ΠΎ Π²ΡΠ²ΠΎΠ΄Π° Π΄Π»Ρ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΠΈ ΠΏΡΠΈΠ½ΡΡΠΈΡ ΡΠ΅ΡΠ΅Π½ΠΈΡ Π² Π·Π°Π΄Π°ΡΠ°Ρ
Π°Π½Π°Π»ΠΈΠ·Π° Π½Π°Π²ΡΠΊΠΎΠ² ΠΈ ΡΠΌΠ΅Π½ΠΈΠΉ ΠΊΠΎΠ½ΡΠΈΠ½Π³Π΅Π½ΡΠ° ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² ΠΈΡΡ
ΠΎΠ΄Ρ ΠΈΠ· ΡΡΠ΅Π±ΠΎΠ²Π°Π½ΠΈΠΉ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΡΡ
ΡΠ°Π±ΠΎΡΠΎΠ΄Π°ΡΠ΅Π»Π΅ΠΉ, Ρ ΡΠ΅Π»ΡΡ ΡΠΌΠ΅Π½ΡΡΠ΅Π½ΠΈΡ Π²ΡΠ΅ΠΌΠ΅Π½ΠΈ Π½Π° ΠΏΠ΅ΡΠ²ΠΈΡΠ½ΡΡ ΠΎΠ±ΡΠ°Π±ΠΎΡΠΊΡ ΠΈΠ½ΡΠΎΡΠΌΠ°ΡΠΈΠΈ ΠΊΠ°ΡΠ°ΡΠ΅Π»ΡΠ½ΠΎ ΠΏΠΎΡΠ΅Π½ΡΠΈΠ°Π»ΡΠ½ΡΡ
ΠΊΠ°Π½Π΄ΠΈΠ΄Π°ΡΠΎΠ² Π½Π° Π²Π°ΠΊΠ°Π½ΡΠ½ΡΡ Π΄ΠΎΠ»ΠΆΠ½ΠΎΡΡΡ. ΠΡΠΈ Π°Π½Π°Π»ΠΈΠ·Π΅ ΡΠ΅Π·ΡΠ»ΡΡΠ°ΡΠΎΠ² ΠΎΡΠ΅Π½ΠΊΠΈ ΠΊΠΎΠΌΠΏΠ΅ΡΠ΅Π½ΡΠ½ΠΎΡΡΠΈ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² Π²ΡΠ·ΠΎΠ² Π²ΠΎΠ·Π½ΠΈΠΊΠ°Π΅Ρ ΠΎΠΏΡΠ΅Π΄Π΅Π»Π΅Π½Π½Π°Ρ ΡΡΠ΅ΠΏΠ΅Π½Ρ Π½Π΅ΡΠ΅ΡΠΊΠΎΡΡΠΈ. Π ΡΠΎΠ²ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ ΠΏΡΠ°ΠΊΡΠΈΠΊΠ΅ Π½Π΅ΡΠ΅ΡΠΊΠ°Ρ Π»ΠΎΠ³ΠΈΠΊΠ° ΠΏΡΠΈΠΌΠ΅Π½ΡΠ΅ΡΡΡ Π²ΠΎ ΠΌΠ½ΠΎΠ³ΠΈΡ
ΡΠ°Π·Π»ΠΈΡΠ½ΡΡ
ΠΌΠ΅ΡΠΎΠ΄Π°Ρ
ΠΎΡΠ΅Π½ΠΊΠΈ, Π² ΡΠΎΠΌ ΡΠΈΡΠ»Π΅ Π°Π½ΠΊΠ΅ΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅, ΠΈΠ½ΡΠ΅ΡΠ²ΡΡ, ΡΠ΅ΡΡΠΈΡΠΎΠ²Π°Π½ΠΈΠ΅, ΠΎΠΏΠΈΡΠ°ΡΠ΅Π»ΡΠ½ΡΠΉ ΠΌΠ΅ΡΠΎΠ΄, ΠΌΠ΅ΡΠΎΠ΄ ΠΊΠ»Π°ΡΡΠΈΡΠΈΠΊΠ°ΡΠΈΠΈ, ΠΏΠ°ΡΠ½ΠΎΠ΅ ΡΡΠ°Π²Π½Π΅Π½ΠΈΠ΅, ΡΠ΅ΠΉΡΠΈΠ½Π³ΠΎΠ²ΡΠΉ ΠΌΠ΅ΡΠΎΠ΄, Π΄Π΅Π»ΠΎΠ²ΡΠ΅ ΠΈΠ³ΡΡ ΠΌΠΎΠ΄Π΅Π»ΠΈ ΠΊΠΎΠΌΠΏΠ΅ΡΠ΅Π½ΡΠ½ΠΎΡΡΠΈ ΠΈ ΡΠΎΠΌΡ ΠΏΠΎΠ΄ΠΎΠ±Π½ΠΎΠ΅. ΠΠ°ΠΆΠ΄ΡΠΉ ΠΈΠ· ΠΌΠ΅ΡΠΎΠ΄ΠΎΠ² ΠΈΠΌΠ΅Π΅Ρ ΡΠ²ΠΎΠΈ ΠΏΡΠ΅ΠΈΠΌΡΡΠ΅ΡΡΠ²Π° ΠΈ Π½Π΅Π΄ΠΎΡΡΠ°ΡΠΊΠΈ, Π½ΠΎ ΡΡΡΠ΅ΠΊΡΠΈΠ²Π½Ρ ΠΎΠ½ΠΈ ΡΠΎΠ»ΡΠΊΠΎ Π² ΡΠΎΡΡΠ°Π²Π΅ Π΅Π΄ΠΈΠ½ΠΎΠΉ ΡΠΈΡΡΠ΅ΠΌΡ ΡΠΏΡΠ°Π²Π»Π΅Π½ΠΈΡ ΠΏΠ΅ΡΡΠΎΠ½Π°Π»ΠΎΠΌ. ΠΠ°ΠΊ ΠΌΠ΅ΡΠΎΠ΄ Π΄Π»Ρ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΠΈ ΡΠΈΡΡΠ΅ΠΌΠ½ΠΎΠ³ΠΎ ΠΏΠΎΠ΄Ρ
ΠΎΠ΄Π° ΠΊ ΠΎΡΠ΅Π½ΠΊΠ΅ ΠΊΠΎΠ½ΡΠΈΠ½Π³Π΅Π½ΡΠ° ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² ΠΏΡΠ΅Π΄Π»ΠΎΠΆΠ΅Π½ΠΎ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°ΡΡ Π½Π΅ΡΠ΅ΡΠΊΡΡ Π»ΠΎΠ³ΠΈΠΊΡ, ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°ΠΏΠΏΠ°ΡΠ°Ρ, ΠΊΠΎΡΠΎΡΡΠΉ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΏΠΎΡΡΡΠΎΠΈΡΡ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΎΠ±ΡΠ΅ΠΊΡΠ°, ΠΎΡΠ½ΠΎΠ²Π°Π½Π½ΡΡ Π½Π° Π½Π΅ΡΠ΅ΡΠΊΠΈΡ
ΡΡΠΆΠ΄Π΅Π½ΠΈΡΡ
. ΠΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΠ΅ Π½Π΅ΡΠ΅ΡΠΊΠΎΠΉ Π»ΠΎΠ³ΠΈΠΊΠΈ, ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΡΠ΅ΡΠΊΠΈΠΉ Π°ΠΏΠΏΠ°ΡΠ°Ρ ΠΊΠΎΡΠΎΡΠΎΠΉ ΠΏΠΎΠ·Π²ΠΎΠ»ΡΠ΅Ρ ΠΏΠΎΡΡΡΠΎΠΈΡΡ ΠΌΠΎΠ΄Π΅Π»Ρ ΠΎΠ±ΡΠ΅ΠΊΡΠ°, ΠΎΡΠ½ΠΎΠ²ΡΠ²Π°ΡΡΡ Π½Π° Π½Π΅ΡΠ΅ΡΠΊΠΈΡ
ΡΠ°ΡΡΡΠΆΠ΄Π΅Π½ΠΈΡΡ
ΠΈ ΠΏΡΠ°Π²ΠΈΠ»Π°Ρ
. ΠΠ°ΠΆΠ½Π΅ΠΉΡΠ΅Π΅ ΡΡΠ»ΠΎΠ²ΠΈΠ΅ ΡΠΎΠ·Π΄Π°Π½ΠΈΡ ΡΠ°ΠΊΠΎΠΉ ΠΌΠΎΠ΄Π΅Π»ΠΈ Π·Π°ΠΊΠ»ΡΡΠ°Π΅ΡΡΡ Π² ΡΠΎΠΌ, ΡΡΠΎΠ±Ρ ΠΏΠ΅ΡΠ΅Π²Π΅ΡΡΠΈ Π½Π΅ΡΠ΅ΡΠΊΠΈΠ΅, ΠΊΠ°ΡΠ΅ΡΡΠ²Π΅Π½Π½ΡΠ΅ ΠΎΡΠ΅Π½ΠΊΠΈ, ΠΏΡΠΈΠΌΠ΅Π½ΡΠ΅ΠΌΡΠ΅ ΡΠ΅Π»ΠΎΠ²Π΅ΠΊΠΎΠΌ, Π½Π° ΡΠ·ΡΠΊ ΠΌΠ°ΡΠ΅ΠΌΠ°ΡΠΈΠΊΠΈ, ΠΊΠΎΡΠΎΡΠ°Ρ Π±ΡΠ΄Π΅Ρ ΠΏΠΎΠ½ΡΡΠ½Π° Π²ΡΡΠΈΡΠ»ΠΈΡΠ΅Π»ΡΠ½ΠΎΠΉ ΠΌΠ°ΡΠΈΠ½Π΅. ΠΠ°ΠΈΠ±ΠΎΠ»Π΅Π΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΡΠ΅ΠΌΡΠΌΠΈ ΡΠ²Π»ΡΡΡΡΡ Π½Π΅ΡΠ΅ΡΠΊΠΈΠ΅ Π²ΡΠ²ΠΎΠ΄Ρ Ρ ΠΏΠΎΠΌΠΎΡΡΡ ΡΠΏΠΎΡΠΎΠ±ΠΎΠ² ΠΠ°ΠΌΠ΄Π°Π½ΠΈ ΠΈ Π‘ΡΠ³Π΅Π½ΠΎ. Π Π½Π΅ΡΠ΅ΡΠΊΠΎΠΌ Π²ΡΠ²ΠΎΠ΄Π΅ ΡΠΈΠΏΠ° ΠΠ°ΠΌΠ΄Π°Π½ΠΈ Π·Π½Π°ΡΠ΅Π½ΠΈΠ΅ Π²ΡΡ
ΠΎΠ΄Π½ΠΎΠΉ ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΠΎΠΉ Π·Π°Π΄Π°ΡΡΡΡ Π½Π΅ΡΠ΅ΡΠΊΠΈΠΌΠΈ ΡΠ΅ΡΠΌΠ°ΠΌΠΈ, Π² Π·Π°ΠΊΠ»ΡΡΠ΅Π½ΠΈΠΈ ΡΠΈΠΏΠ° Π‘ΡΠ³Π΅Π½ΠΎ β ΠΊΠ°ΠΊ Π»ΠΈΠ½Π΅ΠΉΠ½Π°Ρ ΠΊΠΎΠΌΠ±ΠΈΠ½Π°ΡΠΈΡ Π²Ρ
ΠΎΠ΄Π½ΡΡ
ΠΏΠ΅ΡΠ΅ΠΌΠ΅Π½Π½ΡΡ
. ΠΡΡΠ»Π΅Π΄ΠΎΠ²Π°Π½ΠΈΡ Π² ΠΎΠ±Π»Π°ΡΡΠΈ ΠΏΡΠΈΠΌΠ΅Π½Π΅Π½ΠΈΡ Π½Π΅ΡΠ΅ΡΠΊΠΎΠΉ Π»ΠΎΠ³ΠΈΠΊΠΈ Π² ΡΠΎΡΠΈΠΎΡΠΊΠΎΠ½ΠΎΠΌΠΈΡΠ΅ΡΠΊΠΈΡ
ΡΠΈΡΡΠ΅ΠΌΠ°Ρ
ΠΏΠΎΠ·Π²ΠΎΠ»ΡΡΡ Π³ΠΎΠ²ΠΎΡΠΈΡΡ ΠΎ Π²ΠΎΠ·ΠΌΠΎΠΆΠ½ΠΎΡΡΠΈ Π΅Π΅ ΠΈΡΠΏΠΎΠ»ΡΠ·ΠΎΠ²Π°Π½ΠΈΡ Π΄Π»Ρ ΠΎΡΠ΅Π½ΠΊΠΈ ΠΊΠΎΠΌΠΏΠ΅ΡΠ΅Π½ΡΠΈΠΉ ΡΡΡΠ΄Π΅Π½ΡΠΎΠ² Π²ΡΠ·ΠΎΠ²
Fuzzy Logic and Corporate Governance Theories
[Excerpt] βFuzzy logic is a theory that categorizes concepts or things belonging to more than one group. A methodology that explains how things function in multiple groups (not fully in one group or another) offers advantages when no one definition or membership in a group accounts for belonging to multiple groups. The principal/agent model of corporate governance has some characteristics of fuzzy logic theory.
Under traditional agency theory of corporate governance, shareholders, directors, and senior corporate officers each belong to groups having multiple attributes. In the principal/agent model of corporate governance, shareholders are owners or principals; directors are shareholders and agents of the corporation; and senior corporate officers are directorsβ agents, shareholdersβ agents, and agents of the corporation. Each one functions within multiple groups serving multiple agency roles, and each owes fiduciary duties that vary depending on whose agent they are functioning as.
Such a multi-dimensional role for corporate actors is a consequence of multi-definitional corporate purpose within agency theory of governance. This multi-dimensional group membership is not easily reconciled within agency theory and is therefore not always explained. However, traditional corporate governance theory can borrow another basic tenet of fuzzy logic theory. Fuzzy theory not only accounts for membership in multiple groups, but also explains how things work because they are multidimensional or ambiguous. This article seeks to explain the ambiguities of corporate governance theory and suggests a framework that accounts for the multi-agent role of senior corporate officers of public companies. It offers a kind of fuzzy logic theory for understanding the fiduciary duties of senior officers.
The purpose of this article is to evaluate other models of corporate governance that account for the multi-agent role of senior officers of public companies and assess the ability of various models to hold senior officers accountable to the corporation.
- β¦