Class information for:
Level 1: FUSION RULE ESTIMATION//WOOD INSPECTION//CRUDE TOWER

Basic class information
Class id #P Avg. number of
references		 Database coverage
of references
32522 138 23.4 42%


Bar chart of Publication_year

Last years might be incomplete

Hierarchy of classes
The table includes all classes above and classes immediately below the current class.


Cluster id Level Cluster label #P
12 4 POLYMER SCIENCE//MATERIALS SCIENCE, PAPER & WOOD//CHEMISTRY, PHYSICAL 1084170
137 3       MATERIALS SCIENCE, PAPER & WOOD//TAPPI JOURNAL//HOLZFORSCHUNG 65468
150 2             MATERIALS SCIENCE, PAPER & WOOD//FOREST PRODUCTS JOURNAL//FORESTRY 23095
32522 1                   FUSION RULE ESTIMATION//WOOD INSPECTION//CRUDE TOWER 138

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 FUSION RULE ESTIMATION authKW 708069 3% 80% 4
2 WOOD INSPECTION authKW 505761 3% 57% 4
3 CRUDE TOWER authKW 442544 1% 100% 2
4 WOOD VENEER INSPECTION authKW 442544 1% 100% 2
5 OF TECHNOL address 331905 2% 50% 3
6 WOOD SPECIES IDENTIFICATION authKW 331905 2% 50% 3
7 CONSTRUCCIONES ARQUITECTON CONTROL address 295028 1% 67% 2
8 ARTIFICIAL NEURAL NETWORK DESIGN authKW 221272 1% 100% 1
9 ARTVIN VOCAT address 221272 1% 100% 1
10 AUTHENTICATION OF COINS authKW 221272 1% 100% 1

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 Materials Science, Paper & Wood 2304 15% 0% 21
2 Forestry 1425 18% 0% 25
3 Computer Science, Artificial Intelligence 489 16% 0% 22
4 Automation & Control Systems 361 11% 0% 15
5 Engineering, Marine 201 2% 0% 3
6 Engineering, Manufacturing 142 6% 0% 8
7 Engineering, Mechanical 136 11% 0% 15
8 Engineering, General 135 8% 0% 11
9 Instruments & Instrumentation 106 9% 0% 13
10 Engineering, Ocean 89 2% 0% 3

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 OF TECHNOL 331905 2% 50% 3
2 CONSTRUCCIONES ARQUITECTON CONTROL 295028 1% 67% 2
3 ARTVIN VOCAT 221272 1% 100% 1
4 COLEGIO LICACAO COLUNI 221272 1% 100% 1
5 COMPUTAT INTELLIGENCE TECHNOL GRP 221272 1% 100% 1
6 ENTERPRISE QUAL MANAGEMENT 221272 1% 100% 1
7 INGN CIVIL TECNOL CONSTRUCCIAN 221272 1% 100% 1
8 INGN ESTRUCT MECAN MAT COMPUESTOS 221272 1% 100% 1
9 MANAGEMENT SCI INFORMAT TECHNOL 0235 221272 1% 100% 1
10 CATEDRA CONSTRUCC 3 221270 1% 50% 2

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 INTECH 30778 3% 3% 4
2 PROCESS CONTROL AND QUALITY 13634 2% 2% 3
3 INVESTIGACION AGRARIA-SISTEMAS Y RECURSOS FORESTALES 11200 1% 3% 2
4 PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART E-JOURNAL OF PROCESS MECHANICAL ENGINEERING 10103 4% 1% 5
5 JOURNAL OF FORESTRY RESEARCH 6853 3% 1% 4
6 EUROPEAN JOURNAL OF WOOD AND WOOD PRODUCTS 2815 2% 0% 3
7 ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE 2159 4% 0% 5
8 HOLZFORSCHUNG 1609 4% 0% 5
9 COMPUTERS AND ELECTRONICS IN AGRICULTURE 1435 3% 0% 4
10 HYDROCARBON PROCESSING 1425 2% 0% 3

Author Key Words


Rank Term Chi square Shr. of publ. in
class containing
term		 Class's shr. of
term's tot. occurrences		 #P with
term in
class		 LCSH search Wikipedia search
1 FUSION RULE ESTIMATION 708069 3% 80% 4 Search FUSION+RULE+ESTIMATION Search FUSION+RULE+ESTIMATION
2 WOOD INSPECTION 505761 3% 57% 4 Search WOOD+INSPECTION Search WOOD+INSPECTION
3 CRUDE TOWER 442544 1% 100% 2 Search CRUDE+TOWER Search CRUDE+TOWER
4 WOOD VENEER INSPECTION 442544 1% 100% 2 Search WOOD+VENEER+INSPECTION Search WOOD+VENEER+INSPECTION
5 WOOD SPECIES IDENTIFICATION 331905 2% 50% 3 Search WOOD+SPECIES+IDENTIFICATION Search WOOD+SPECIES+IDENTIFICATION
6 ARTIFICIAL NEURAL NETWORK DESIGN 221272 1% 100% 1 Search ARTIFICIAL+NEURAL+NETWORK+DESIGN Search ARTIFICIAL+NEURAL+NETWORK+DESIGN
7 AUTHENTICATION OF COINS 221272 1% 100% 1 Search AUTHENTICATION+OF+COINS Search AUTHENTICATION+OF+COINS
8 AUTOMATIC CLASSIFICATION OF WOOD 221272 1% 100% 1 Search AUTOMATIC+CLASSIFICATION+OF+WOOD Search AUTOMATIC+CLASSIFICATION+OF+WOOD
9 AUTOMATIC SPECTRA ANALYSIS 221272 1% 100% 1 Search AUTOMATIC+SPECTRA+ANALYSIS Search AUTOMATIC+SPECTRA+ANALYSIS
10 AUTOMATIC WOOD CLASSIFICATION 221272 1% 100% 1 Search AUTOMATIC+WOOD+CLASSIFICATION Search AUTOMATIC+WOOD+CLASSIFICATION

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 OZSAHIN, S , (2013) OPTIMIZATION OF PROCESS PARAMETERS IN ORIENTED STRAND BOARD MANUFACTURING WITH ARTIFICIAL NEURAL NETWORK ANALYSIS.EUROPEAN JOURNAL OF WOOD AND WOOD PRODUCTS. VOL. 71. ISSUE 6. P. 769-777 26 70% 6
2 WATANABE, K , KORAI, H , MATSUSHITA, Y , HAYASHI, T , (2015) PREDICTING INTERNAL BOND STRENGTH OF PARTICLEBOARD UNDER OUTDOOR EXPOSURE BASED ON CLIMATE DATA: COMPARISON OF MULTIPLE LINEAR REGRESSION AND ARTIFICIAL NEURAL NETWORK.JOURNAL OF WOOD SCIENCE. VOL. 61. ISSUE 2. P. 151 -158 17 61% 2
3 OZSAHIN, S , AYDIN, I , (2014) PREDICTION OF THE OPTIMUM VENEER DRYING TEMPERATURE FOR GOOD BONDING IN PLYWOOD MANUFACTURING BY MEANS OF ARTIFICIAL NEURAL NETWORK.WOOD SCIENCE AND TECHNOLOGY. VOL. 48. ISSUE 1. P. 59 -70 14 74% 1
4 OZSAHIN, S , (2012) THE USE OF AN ARTIFICIAL NEURAL NETWORK FOR MODELING THE MOISTURE ABSORPTION AND THICKNESS SWELLING OF ORIENTED STRAND BOARD.BIORESOURCES. VOL. 7. ISSUE 1. P. 1053-1067 17 53% 9
5 SOFUOGLU, SD , (2015) USING ARTIFICIAL NEURAL NETWORKS TO MODEL THE SURFACE ROUGHNESS OF MASSIVE WOODEN EDGE-GLUED PANELS MADE OF SCOTCH PINE (PINUS SYLVESTRIS L.) IN A MACHINING PROCESS WITH COMPUTER NUMERICAL CONTROL.BIORESOURCES. VOL. 10. ISSUE 4. P. 6797 -6808 14 58% 1
6 ESTEBAN, LG , FERNANDEZ, FG , DE PALACIOS, P , (2011) PREDICTION OF PLYWOOD BONDING QUALITY USING AN ARTIFICIAL NEURAL NETWORK.HOLZFORSCHUNG. VOL. 65. ISSUE 2. P. 209 -214 13 59% 14
7 TIRYAKI, S , MALKOCOGLU, A , OZSAHIN, S , (2014) USING ARTIFICIAL NEURAL NETWORKS FOR MODELING SURFACE ROUGHNESS OF WOOD IN MACHINING PROCESS.CONSTRUCTION AND BUILDING MATERIALS. VOL. 66. ISSUE . P. 329 -335 13 48% 2
8 TIRYAKI, S , OZSAHIN, S , YILDIRIM, I , (2014) COMPARISON OF ARTIFICIAL NEURAL NETWORK AND MULTIPLE LINEAR REGRESSION MODELS TO PREDICT OPTIMUM BONDING STRENGTH OF HEAT TREATED WOODS.INTERNATIONAL JOURNAL OF ADHESION AND ADHESIVES. VOL. 55. ISSUE . P. 29 -36 14 44% 2
9 TIRYAKI, S , BARDAK, S , BARDAK, T , (2015) EXPERIMENTAL INVESTIGATION AND PREDICTION OF BONDING STRENGTH OF ORIENTAL BEECH (FAGUS ORIENTALIS LIPSKY) BONDED WITH POLYVINYL ACETATE ADHESIVE.JOURNAL OF ADHESION SCIENCE AND TECHNOLOGY. VOL. 29. ISSUE 23. P. 2521 -2536 15 38% 1
10 YAPICI, F , ESEN, R , ERKAYMAZ, O , BAS, H , (2015) MODELING OF COMPRESSIVE STRENGTH PARALLEL TO GRAIN OF HEAT TREATED SCOTCH PINE (PINUS SYLVESTRIS L.) WOOD BY USING ARTIFICIAL NEURAL NETWORK.DRVNA INDUSTRIJA. VOL. 66. ISSUE 4. P. 347 -352 8 62% 0

Classes with closest relation at Level 1


Rank Class id link
1 37230 PALLET LOGISTICS//CARBON EQUIVALENT EMISSIONS//BUY SELL PALLET PROGRAMS
2 15856 WOOD MACHINING//BANDSAWING//WOOD MACHINING TOOLING PROGRAM
3 36433 ARYLPROPARGYL ETHERS OF PHENOLS//CHEMOMETR//SUPERVISED KOHONEN NETWORKS
4 7791 DEFECT DETECTION//SURFACE INSPECTION//FABRIC DEFECTS
5 21381 ADHESIVE PENETRATION//WOOD BASED COMPOSITES//MAT SCI PROC ENGN
6 29031 WOOD IDENTIFICATION//TIMBER TRACKING//DIPTEROCARPOIDEAE
7 23369 LAMINATED VENEER LUMBER LVL//LATHE CHECKS//LAMINATED VENEER LUMBER
8 29350 GREAT EAGLE 25F//MOBILE CONTROL AND MONITORING//PROACTIVE TASK SUPPORT
9 4965 PARTICLEBOARD//MATERIALS SCIENCE, PAPER & WOOD//THICKNESS SWELLING
10 1731 WOOD DENSITY//WOOD QUALITY//FORESTRY

Go to start page