Probabilistic Scheduling Based On Hybrid Bayesian Network–Program Evaluation Review Technique,

نویسندگان

چکیده

Project scheduling based on probabilistic methods commonly uses the Program Evaluation Review Technique (PERT). However, practitioners do not widely utilize PERT-based due to difficulty in obtaining historical data for similar projects. PERT has several drawbacks, such as inability update activity dura- tions real time. In reality, changes project conditions related resources have a highly dynamic nature. The availability of materials, fluctuating labor productiv- ity, and equipment significantly determine completion This research aims propose model Hybrid Bayesian Network-PERT. combines with Network (BN). BN is used accommodate real-time resource conditions. modeling diagrams variables obtained through an in-depth literature review, direct field observations, distributing questionnaires experts scheduling. validated by applying proposed 60 m concrete bridge construction Indonesia. simulation results are then compared case study assess model’s accuracy. result shows that hybrid Bayesian-PERT accurate can eliminate weaknesses method. Besides being able provide prediction time (93.4%), this also be updated according actual condition

برای دانلود باید عضویت طلایی داشته باشید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Probabilistic Inference for Hybrid Bayesian Networks

A Bayesian network (BN) Charniak (1991) Pearl (1988) Jensen (1996) Neapolitan (1990) is a directed acyclic graph (DAG) consisting of nodes and arrows, in which node represents random variables, and arrow represents dependence relationship between connected nodes in the sense of the probabilistic, deterministic, or functional. Each node in BN has a specified conditional probability distribution ...

متن کامل

Review of Neighbor Coverage Based Probabilistic Rebroadcast with Cryptographic Technique

Mobile Ad Hoc Network (MANETs) consists of a collection of mobile nodes which can move freely. These nodes have characteristic that they can be dynamically selforganized into arbitrary topology networks without a fixed infrastructure. MANETs are highly dynamic network because nodes may join and leave the network at any time. NCPR significantly reduce the routing overhead in the MANET. Once the ...

متن کامل

Biometric Iris Recognition Based on Hybrid Technique

Iris Recognition is one of the important biometric recognition systems that identify people based on their eyes and iris. In this paper the iris recognition algorithm is implemented via histogram equalization and wavelet techniques. In this paper the iris recognition approach is implemented via many steps, these steps are concentrated on image capturing, enhancement and identification. Differen...

متن کامل

Bayesian speaker adaptation based on probabilistic principal component analysis

In this paper, we propose a Bayesian speaker adaptation technique based on the probabilistic principal component analysis (PPCA). The PPCA is employed to obtain the canonical speaker models which provide the a priori knowledge of the training speakers. The proposed approach is conveniently incorporated into the Bayesian adaptation framework where the parameters are adapted to the new speaker’s ...

متن کامل

Probabilistic Decision Making of Robot Behavior Based on Bayesian Network

This paper presents a technique for an intelligent software robot (sobot) Rity to behave in uncertain environment in an appropriate manner. The intelligence of a robot is necessary to infer an appropriate behavior when various sensor data (stimuli) exist simultaneously and a specific behavior can be decided by a behavior controller. There could be various methods to build a behavior controller....

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

ژورنال

عنوان ژورنال: IPTEK: The Journal for Technology and Science

سال: 2023

ISSN: ['2088-2033', '0853-4098']

DOI: https://doi.org/10.12962/j20882033.v34i2.16693