Class information for: |
Basic class information |
Class id | #P | Avg. number of references |
Database coverage of references |
---|---|---|---|
16964 | 625 | 26.3 | 48% |
Hierarchy of classes |
The table includes all classes above and classes immediately below the current class. |
Cluster id | Level | Cluster label | #P |
---|---|---|---|
16 | 4 | ENGINEERING, CIVIL//CONSTRUCTION & BUILDING TECHNOLOGY//MECHANICS | 627508 |
101 | 3 | CONSTRUCTION & BUILDING TECHNOLOGY//CEMENT AND CONCRETE RESEARCH//ENGINEERING, CIVIL | 73839 |
9 | 2 | CONSTRUCTION & BUILDING TECHNOLOGY//CEMENT AND CONCRETE RESEARCH//CONSTRUCTION AND BUILDING MATERIALS | 39742 |
16964 | 1 | FUNCTIONALLY GRADED STEEL//CRACK DIVIDER//STRAIN GRADIENT PLASTICITY THEORY | 625 |
Terms with highest relevance score |
rank | Term | termType | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|---|
1 | FUNCTIONALLY GRADED STEEL | authKW | 852734 | 4% | 73% | 24 |
2 | CRACK DIVIDER | authKW | 694828 | 3% | 89% | 16 |
3 | STRAIN GRADIENT PLASTICITY THEORY | authKW | 502508 | 2% | 86% | 12 |
4 | CRACK ARRESTER | authKW | 439692 | 2% | 75% | 12 |
5 | STATISTICALLY STORED DISLOCATIONS | authKW | 439692 | 2% | 75% | 12 |
6 | TECH ENGN SCI | address | 375786 | 3% | 38% | 20 |
7 | FUNCTIONALLY GRADED AUSTENITIC STEEL | authKW | 341987 | 1% | 100% | 7 |
8 | SAVEH BRANCH | address | 341257 | 9% | 12% | 57 |
9 | AUSTENITIC FGS | authKW | 293132 | 1% | 100% | 6 |
10 | FERRITIC FGS | authKW | 293132 | 1% | 100% | 6 |
Web of Science journal categories |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | Construction & Building Technology | 33894 | 39% | 0% | 245 |
2 | Engineering, Civil | 13806 | 41% | 0% | 255 |
3 | Computer Science, Interdisciplinary Applications | 3218 | 20% | 0% | 123 |
4 | Computer Science, Artificial Intelligence | 2140 | 16% | 0% | 98 |
5 | Materials Science, Characterization, Testing | 2092 | 7% | 0% | 46 |
6 | Materials Science, Multidisciplinary | 1734 | 38% | 0% | 237 |
7 | Engineering, General | 1078 | 10% | 0% | 65 |
8 | Materials Science, Composites | 266 | 3% | 0% | 20 |
9 | Engineering, Manufacturing | 200 | 3% | 0% | 21 |
10 | Computer Science, Software Engineering | 133 | 4% | 0% | 24 |
Address terms |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | TECH ENGN SCI | 375786 | 3% | 38% | 20 |
2 | SAVEH BRANCH | 341257 | 9% | 12% | 57 |
3 | RINKER | 156335 | 1% | 80% | 4 |
4 | CDMM | 122133 | 1% | 50% | 5 |
5 | GANG NAM GU | 97711 | 0% | 100% | 2 |
6 | CONSTRUCT OCCUPAT HLTH SAFETY | 65139 | 0% | 67% | 2 |
7 | ECOL HAZARD MITIGAT ENGN EARCHING | 62811 | 0% | 43% | 3 |
8 | AEIPLOUS INNOVAT SUSTAINABLE DEV | 48855 | 0% | 100% | 1 |
9 | AEROSP VERT | 48855 | 0% | 100% | 1 |
10 | AUBORN SCI ENGN 431 | 48855 | 0% | 100% | 1 |
Journals |
Rank | Term | Chi square | Shr. of publ. in class containing term |
Class's shr. of term's tot. occurrences |
#P with term in class |
---|---|---|---|---|---|
1 | COMPUTERS AND CONCRETE | 104753 | 6% | 6% | 38 |
2 | JOURNAL OF COMPUTING IN CIVIL ENGINEERING | 22928 | 4% | 2% | 23 |
3 | NEURAL COMPUTING & APPLICATIONS | 20029 | 5% | 1% | 31 |
4 | ACI MATERIALS JOURNAL | 14586 | 4% | 1% | 24 |
5 | CONSTRUCTION AND BUILDING MATERIALS | 13021 | 8% | 1% | 50 |
6 | REVISTA ROMANA DE MATERIALE-ROMANIAN JOURNAL OF MATERIALS | 11342 | 2% | 2% | 10 |
7 | ADVANCES IN ENGINEERING SOFTWARE | 9659 | 3% | 1% | 21 |
8 | INTERNATIONAL JOURNAL OF DAMAGE MECHANICS | 4193 | 1% | 1% | 7 |
9 | CEMENT AND CONCRETE RESEARCH | 4172 | 4% | 0% | 23 |
10 | JOURNAL OF MATERIALS IN CIVIL ENGINEERING | 4046 | 2% | 1% | 15 |
Author Key Words |
Core articles |
The table includes core articles in the class. The following variables is taken into account for the relevance score of an article in a cluster c: (1) Number of references referring to publications in the class. (2) Share of total number of active references referring to publications in the class. (3) Age of the article. New articles get higher score than old articles. (4) Citation rate, normalized to year. |
Rank | Reference | # ref. in cl. |
Shr. of ref. in cl. |
Citations |
---|---|---|---|---|
1 | BOHLOOLI, H , NAZARI, A , KAYKHA, MM , (2013) MICROHARDNESS PROFILE PREDICTION OF FUNCTIONALLY GRADED STEELS BY ARTIFICIAL NEURAL NETWORKS.INTERNATIONAL JOURNAL OF DAMAGE MECHANICS. VOL. 22. ISSUE 1. P. 17 -36 | 49 | 86% | 1 |
2 | NAZARI, A , (2013) APPLICATION OF ARTIFICIAL NEURAL NETWORKS FOR ANALYTICAL MODELING OF CHARPY IMPACT ENERGY OF FUNCTIONALLY GRADED STEELS.NEURAL COMPUTING & APPLICATIONS. VOL. 22. ISSUE 3-4. P. 731 -745 | 47 | 85% | 4 |
3 | NAZARI, A , (2013) ANALYTICAL MODELING OF TENSILE STRENGTH OF FUNCTIONALLY GRADED STEELS.NEURAL COMPUTING & APPLICATIONS. VOL. 23. ISSUE 3-4. P. 787 -799 | 45 | 85% | 0 |
4 | NAZARI, A , KHALAJ, G , RIAHI, S , (2012) APPLICATION OF ANFIS FOR ANALYTICAL MODELING OF J(IC) OF FUNCTIONALLY GRADED STEELS.MATHEMATICAL AND COMPUTER MODELLING. VOL. 55. ISSUE 3-4. P. 1339 -1353 | 39 | 85% | 4 |
5 | NAZARI, A , (2012) APPLICATION OF ANFIS FOR ANALYTICAL MODELING OF TENSILE STRENGTH OF FUNCTIONALLY GRADED STEELS.MATERIALS RESEARCH-IBERO-AMERICAN JOURNAL OF MATERIALS. VOL. 15. ISSUE 3. P. 383 -396 | 37 | 84% | 1 |
6 | BOHLOOLI, H , NAZARI, A , KAYKHA, MM , (2013) PREDICTION MICROHARDNESS PROFILE OF FUNCTIONALLY GRADED STEELS BY ANFIS.NEURAL COMPUTING & APPLICATIONS. VOL. 22. ISSUE 5. P. 847 -858 | 35 | 81% | 0 |
7 | BOHLOOLI, H , NAZARI, A , KAYKHA, MM , (2012) ANALYTICAL MODELING OF CHARPY IMPACT ENERGY OF FUNCTIONALLY GRADED STEELS BY ANFIS.INTERNATIONAL JOURNAL OF DAMAGE MECHANICS. VOL. 21. ISSUE 6. P. 913 -939 | 37 | 79% | 0 |
8 | CHOU, JS , PHAM, AD , (2013) ENHANCED ARTIFICIAL INTELLIGENCE FOR ENSEMBLE APPROACH TO PREDICTING HIGH PERFORMANCE CONCRETE COMPRESSIVE STRENGTH.CONSTRUCTION AND BUILDING MATERIALS. VOL. 49. ISSUE . P. 554-563 | 26 | 74% | 6 |
9 | NAZARI, A , ABDINEJAD, VR , (2013) ARTIFICIAL NEURAL NETWORKS FOR PREDICTION CHARPY IMPACT ENERGY OF AL6061/SICP-LAMINATED NANOCOMPOSITES.NEURAL COMPUTING & APPLICATIONS. VOL. 23. ISSUE 3-4. P. 801-813 | 24 | 71% | 3 |
10 | ACIKGENC, M , ULAS, M , ALYAMAC, KE , (2015) USING AN ARTIFICIAL NEURAL NETWORK TO PREDICT MIX COMPOSITIONS OF STEEL FIBER-REINFORCED CONCRETE.ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING. VOL. 40. ISSUE 2. P. 407 -419 | 27 | 56% | 1 |
Classes with closest relation at Level 1 |