Search Result

18361

Results Found

Relevance

Filter

Newest

Filter

Most Viewed

Filter

Most Downloaded

Filter

Most Cited

Filter

Pages Count

1837

Go To Page

Search Results/Filters    

Filters

Year

Banks



Expert Group











Full-Text


مرکز اطلاعات علمی SID1
اسکوپوس
دانشگاه غیر انتفاعی مهر اروند
ریسرچگیت
strs
Issue Info: 
  • Year: 

    2010
  • Volume: 

    4
  • Issue: 

    2
  • Pages: 

    113-127
Measures: 
  • Citations: 

    0
  • Views: 

    2340
  • Downloads: 

    980
Abstract: 

Designing timetables, for example course timetables in an institute, is one of the most complicated and time-consuming challenges for personnel. Automating it, not only can help the personnel to manage their work better, but also can be considered as a desired sample to assess the ways of planning and to tackle the constraint satisfaction in artificial intelligence. In this paper, GENETIC ALGORITHMS are primarily studied and then it is applied for optimization of an imaginary faculty course timetable. The new designed algorithm is based on keeping the better chromosomes of the population and employing GENETIC operators on the others in order to improve the overall quality of genes. Some other amendments are also carried out to develop a more capable GENETIC algorithm for TT applications, compared to the standard one. According to the tests, the new GA algorithm will be more successful in generating high fidelity TTs which do not break any hard constraint. The proposed ideas, in this approach are applicable in other similar situations.

Yearly Impact:

View 2340

Download 980 Citation 0 Refrence 0
Author(s): 

ASGHARPOUR M.J. | JAVADIAN N.

Issue Info: 
  • Year: 

    2004
  • Volume: 

    17
  • Issue: 

    2 (TRANSACTIONS A: BASICS)
  • Pages: 

    145-156
Measures: 
  • Citations: 

    611
  • Views: 

    100572
  • Downloads: 

    32784
Abstract: 

This paper presents a mathematical model for designing cellular manufacturing systems (CMSs) solved by GENETIC ALGORITHMS. This model assumes a dynamic production, a stochastic demand, routing flexibility, and machine flexibility. CMS is an application of group technology (GT) for clustering parts and machines by means of their operational and / or apparent form similarity in different aspects of design and production. Most previous researches carried out in CMSs have been embodied in static production and deterministic demand states. Due to real situations of a CM model, if includes a great number of variables and restrictions requiring a long period of time, memory, and process power in order to be solved using available software packages and current optimal methods. Therefore, most researchers pay attention to novel methods. One of these methods is GENETIC ALGORITHMS (Gas). GA is a class of stochastic search techniques used for solving the NP-complete problems, such as CMSs. In this paper, a nonlinear integer model of CMS is designed in dynamic and stochastic states. Then, GENETIC algorithm is used to solve the problem and finally computational results are compared to existing optimal solutions in order to validate the efficiency of the proposed algorithm.

Yearly Impact:

View 100572

Download 32784 Citation 611 Refrence 0
Issue Info: 
  • Year: 

    2006
  • Volume: 

    33
  • Issue: 

    1 (43) ELECTRICAL ENGINEERING
  • Pages: 

    13-24
Measures: 
  • Citations: 

    0
  • Views: 

    1552
  • Downloads: 

    461
Abstract: 

This paper presents a new analytical method based on GENETIC ALGORITHMS (GA) for assessing the composite power system annualized reliability indices. In this proposed method, GA intelligently searches the numerous state spaces of a power system to find the most probable states contributing to system failure. A dynamic optimization load flow model is used for evaluation of sampled states. The proposed method is applied to a 6 bus RBTS and 24 bus RTS-96 reliability test system and the obtained result of program are compared with other conventional methods. Eventually the full set of composite system adequacy indices and load bus indices is calculated. The obtained results clearly demonstrate the capability of the proposed technique.

Yearly Impact:

View 1552

Download 461 Citation 0 Refrence 0
گارگاه ها آموزشی
Issue Info: 
  • Year: 

    2017
  • Volume: 

    4
  • Issue: 

    1
  • Pages: 

    104-118
Measures: 
  • Citations: 

    0
  • Views: 

    60694
  • Downloads: 

    20253
Abstract: 

This paper studies the incapacitated P-hub centre problem in a network under decentralized management assuming time as a fuzzy variable. In this network, transport companies act independently, each company makes its route choices according to its own criteria. In this model, time is presented by triangular fuzzy number and used to calculate the fraction of users that probably choose hub routes instead of direct routes. To solve the problem, two GENETIC ALGORITHMS are proposed. The computational results compared with LINGO indicate that the proposed algorithm solves large-scale instances within promising computational time and outperforms LINGO in terms of solution quality.

Yearly Impact:

View 60694

Download 20253 Citation 0 Refrence 0
Author(s): 

CHEN S.M. | CHUNG N.Y.

Issue Info: 
  • Year: 

    2006
  • Volume: 

    21
  • Issue: 

    -
  • Pages: 

    485-501
Measures: 
  • Citations: 

    450
  • Views: 

    21058
  • Downloads: 

    27017
Keywords: 
Abstract: 

Yearly Impact:

View 21058

Download 27017 Citation 450 Refrence 0
Author(s): 

LIU YANFEI

Issue Info: 
  • Year: 

    2000
  • Volume: 

    17
  • Issue: 

    3
  • Pages: 

    429-432
Measures: 
  • Citations: 

    454
  • Views: 

    17417
  • Downloads: 

    27754
Keywords: 
Abstract: 

Yearly Impact:

View 17417

Download 27754 Citation 454 Refrence 0
strs
Author(s): 

PAULINAS M. | USINKAS A.

Issue Info: 
  • Year: 

    2007
  • Volume: 

    36
  • Issue: 

    -
  • Pages: 

    278-284
Measures: 
  • Citations: 

    456
  • Views: 

    20601
  • Downloads: 

    28312
Keywords: 
Abstract: 

Yearly Impact:

View 20601

Download 28312 Citation 456 Refrence 0
Author(s): 

ILEANA I. | ROTAR C. | INCZE A.

Issue Info: 
  • Year: 

    2004
  • Volume: 

    -
  • Issue: 

    -
  • Pages: 

    223-234
Measures: 
  • Citations: 

    457
  • Views: 

    26868
  • Downloads: 

    28498
Keywords: 
Abstract: 

Yearly Impact:

View 26868

Download 28498 Citation 457 Refrence 0
Author(s): 

ALIKHANI H. | Alvanchi A.

Journal: 

SCIENTIA IRANICA

Issue Info: 
  • Year: 

    2019
  • Volume: 

    26
  • Issue: 

    5 (Transactions A: Civil Engineering)
  • Pages: 

    2653-2664
Measures: 
  • Citations: 

    0
  • Views: 

    69844
  • Downloads: 

    51498
Abstract: 

Bridge maintenance activities are often budgeted, scheduled, and conducted for networks of bridges with different ages, types, and conditions, which can make bridge network maintenance management challenging. In this study, we propose an improved maintenance planning model based on GENETIC algorithm for a network of bridges to bring a long-term perspective to the lifespan of bridges. To test the applicability and efficiency of the model, it was applied to a network of 100 bridges in one of the south-western provinces of Iran. The results of the model implementation showed considerable potential for improvement over the currently adopted model for bridge maintenance planning.

Yearly Impact:

View 69844

Download 51498 Citation 0 Refrence 0
Author(s): 

SHIRAZI H.M. | KALAJI Y.

Issue Info: 
  • Year: 

    2010
  • Volume: 

    4
  • Issue: 

    1 (12)
  • Pages: 

    33-43
Measures: 
  • Citations: 

    0
  • Views: 

    71475
  • Downloads: 

    49155
Abstract: 

The reports show a rapid growth in the numbers of attacks to the information and communication systems. Also, we witness smarter behaviors from the attackers. Thus, to prevent our systems from these attackers, we need to create smarter intrusion detection systems. In this paper, a new intelligent intrusion detection system has been proposed using GENETIC ALGORITHMS. In this system, at first, the network connection features were ranked according to their importance in detecting attack using information theory measures. Then, the network traffic linear classifiers based on GENETIC ALGORITHMS have been designed. These classifiers were trained and tested using KDD99 data sets. A detection engine based on these classifiers was build and experimented. The experimental results showed a detection rate up to 92.94%. This engine can be used in real-time mode.

Yearly Impact:

View 71475

Download 49155 Citation 0 Refrence 3220
litScript