Class information for: |
Basic class information |
Class id | #P | Avg. number of references |
Database coverage of references |
---|---|---|---|
12929 | 871 | 21.4 | 54% |
Hierarchy of classes |
The table includes all classes above and classes immediately below the current class. |
Cluster id | Level | Cluster label | #P |
---|---|---|---|
18 | 4 | THERMODYNAMICS//ENERGY & FUELS//ENGINEERING, CHEMICAL | 531182 |
283 | 3 | POWDER TECHNOLOGY//ENGINEERING, CHEMICAL//FLUIDIZATION | 42723 |
1005 | 2 | STIRRED TANK//STIRRED VESSEL//MIXING | 10375 |
12929 | 1 | STACKED NEURAL NETWORKS//EXTRACTIVE ALCOHOLIC FERMENTATION//ALCOHOLIC FERMENTATION PROCESS | 871 |
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 | STACKED NEURAL NETWORKS | authKW | 160251 | 1% | 57% | 8 |
2 | EXTRACTIVE ALCOHOLIC FERMENTATION | authKW | 112179 | 0% | 80% | 4 |
3 | ALCOHOLIC FERMENTATION PROCESS | authKW | 105169 | 0% | 100% | 3 |
4 | DIRECT AND INVERSE NEURAL NETWORK MODELING | authKW | 105169 | 0% | 100% | 3 |
5 | HYBRID NEURAL MODEL | authKW | 105169 | 0% | 100% | 3 |
6 | HYBRID NEURAL MODELLING | authKW | 105169 | 0% | 100% | 3 |
7 | PROJECTIVE ADAPTIVE RESONANCE THEORY | authKW | 105169 | 0% | 100% | 3 |
8 | HYBRID MODELING | authKW | 93070 | 2% | 15% | 18 |
9 | MULTIPLE NEURAL NETWORKS | authKW | 90138 | 1% | 43% | 6 |
10 | FUNCTIONAL LINK NETWORKS | authKW | 79668 | 1% | 45% | 5 |
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 | Engineering, Chemical | 9102 | 43% | 0% | 371 |
2 | Biotechnology & Applied Microbiology | 6381 | 37% | 0% | 318 |
3 | Food Science & Technology | 1559 | 16% | 0% | 141 |
4 | Automation & Control Systems | 782 | 7% | 0% | 57 |
5 | Computer Science, Interdisciplinary Applications | 735 | 8% | 0% | 73 |
6 | Computer Science, Artificial Intelligence | 654 | 8% | 0% | 67 |
7 | Computer Science, Theory & Methods | 81 | 3% | 0% | 29 |
8 | Engineering, General | 47 | 2% | 0% | 20 |
9 | Mathematical & Computational Biology | 23 | 1% | 0% | 11 |
10 | Engineering, Environmental | 21 | 2% | 0% | 16 |
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 | GEN CHEM BIOSYST | 78875 | 0% | 75% | 3 |
2 | BIOPROC CHEM PROC DEV | 70113 | 0% | 100% | 2 |
3 | SERV BIOTECHNOL CELLULES ANIM | 70113 | 0% | 100% | 2 |
4 | PROC ANAL CHEMOMETR CONTROL | 56085 | 0% | 40% | 4 |
5 | PROC ANALYT CONTROL TECHNOL | 45592 | 1% | 12% | 11 |
6 | DPQ | 45063 | 1% | 21% | 6 |
7 | ABT H1 2 | 35056 | 0% | 100% | 1 |
8 | ABT HI2 | 35056 | 0% | 100% | 1 |
9 | AREA TECNOL ALIMENTOS ETS INGENIARIAS AGRARIAS | 35056 | 0% | 100% | 1 |
10 | BIOINTEGRATED PROC GRP AMRI | 35056 | 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 | BIOPROCESS ENGINEERING | 42076 | 4% | 3% | 38 |
2 | COMPUTERS & CHEMICAL ENGINEERING | 21579 | 7% | 1% | 63 |
3 | SEIBUTSU-KOGAKU KAISHI-JOURNAL OF THE SOCIETY FOR FERMENTATION AND BIOENGINEERING | 16995 | 1% | 7% | 7 |
4 | HAKKOKOGAKU KAISHI-JOURNAL OF THE SOCIETY OF FERMENTATION TECHNOLOGY | 16528 | 1% | 4% | 12 |
5 | JOURNAL OF FERMENTATION AND BIOENGINEERING | 11542 | 3% | 1% | 27 |
6 | SEIBUTSU-KOGAKU KAISHI | 10032 | 1% | 4% | 7 |
7 | BRAZILIAN JOURNAL OF CHEMICAL ENGINEERING | 8223 | 2% | 1% | 17 |
8 | BIOPROCESS AND BIOSYSTEMS ENGINEERING | 6164 | 2% | 1% | 18 |
9 | BIOTECH FORUM EUROPE | 4378 | 0% | 6% | 2 |
10 | BIOTECHNOLOGY TECHNIQUES | 3420 | 1% | 1% | 12 |
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 | VON STOSCH, M , OLIVEIRA, R , PERES, J , DE AZEVEDO, SF , (2014) HYBRID SEMI-PARAMETRIC MODELING IN PROCESS SYSTEMS ENGINEERING: PAST, PRESENT AND FUTURE.COMPUTERS & CHEMICAL ENGINEERING. VOL. 60. ISSUE . P. 86 -101 | 86 | 61% | 4 |
2 | HORIUCHI, JI , (2002) FUZZY MODELING AND CONTROL OF BIOLOGICAL PROCESSES.JOURNAL OF BIOSCIENCE AND BIOENGINEERING. VOL. 94. ISSUE 6. P. 574-578 | 34 | 92% | 27 |
3 | SHIOYA, S , SHIMIZU, K , YOSHIDA, T , (1999) KNOWLEDGE-BASED DESIGN AND OPERATION OF BIOPROCESS SYSTEMS.JOURNAL OF BIOSCIENCE AND BIOENGINEERING. VOL. 87. ISSUE 3. P. 261-266 | 39 | 74% | 26 |
4 | HONDA, H , KOBAYASHI, T , (2000) FUZZY CONTROL OF BIOPROCESS.JOURNAL OF BIOSCIENCE AND BIOENGINEERING. VOL. 89. ISSUE 5. P. 401 -408 | 26 | 87% | 19 |
5 | PIULEAC, CG , CURTEANU, S , (2010) DIFFERENT METHODS OF NEURAL NETWORK BASED MODELLING FOR POLYMERIZATION PROCESS.MATERIALE PLASTICE. VOL. 47. ISSUE 3. P. 311-318 | 18 | 82% | 0 |
6 | CURTEANU, S , LEON, F , (2006) HYBRID NEURAL NETWORK MODELS APPLIED TO A FREE RADICAL POLYMERIZATION PROCESS.POLYMER-PLASTICS TECHNOLOGY AND ENGINEERING. VOL. 45. ISSUE 9. P. 1013-1023 | 15 | 94% | 8 |
7 | CURTEANU, S , PETRILA, C , (2006) NEURAL NETWORK-BASED MODELING FOR SEMI-BATCH AND NONISOTHERMAL FREE RADICAL POLYMERIZATION.INTERNATIONAL JOURNAL OF QUANTUM CHEMISTRY. VOL. 106. ISSUE 6. P. 1445-1456 | 17 | 81% | 10 |
8 | NOOR, RAM , AHMAD, Z , DON, MM , UZIR, MH , (2010) MODELLING AND CONTROL OF DIFFERENT TYPES OF POLYMERIZATION PROCESSES USING NEURAL NETWORKS TECHNIQUE: A REVIEW.CANADIAN JOURNAL OF CHEMICAL ENGINEERING. VOL. 88. ISSUE 6. P. 1065 -1084 | 24 | 47% | 20 |
9 | TOMINAGA, O , ITO, F , HANAI, T , HONDA, H , KOBAYASHI, T , (2002) MODELING OF CONSUMERS' PREFERENCES FOR REGULAR COFFEE SAMPLES AND ITS APPLICATION TO PRODUCT DESIGN.FOOD SCIENCE AND TECHNOLOGY RESEARCH. VOL. 8. ISSUE 3. P. 281-285 | 14 | 100% | 3 |
10 | FONSECA, EF , ALVES, TLM , LIMA, EL , DE SOUZA, MB , (2004) A HYBRID NEURAL MODEL FOR THE PRODUCTION OF SORBITOL AND GLUCONIC ACID USING IMMOBILIZED ZYMOMONAS MOBILIS CELLS.LATIN AMERICAN APPLIED RESEARCH. VOL. 34. ISSUE 3. P. 187-193 | 17 | 74% | 4 |
Classes with closest relation at Level 1 |