Class information for: |
Basic class information |
Class id | #P | Avg. number of references |
Database coverage of references |
---|---|---|---|
5908 | 1560 | 27.3 | 52% |
Hierarchy of classes |
The table includes all classes above and classes immediately below the current class. |
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 | LOAD FORECASTING | authKW | 2904462 | 14% | 70% | 211 |
2 | SHORT TERM LOAD FORECASTING | authKW | 2757200 | 10% | 88% | 161 |
3 | ELECTRIC LOAD FORECASTING | authKW | 576479 | 2% | 82% | 36 |
4 | SHORT TERM LOAD FORECASTING STLF | authKW | 250518 | 1% | 80% | 16 |
5 | ELECTRICITY LOAD FORECASTING | authKW | 213114 | 1% | 78% | 14 |
6 | ELECTRICITY DEMAND FORECASTING | authKW | 209694 | 1% | 71% | 15 |
7 | LONG TERM LOAD FORECASTING | authKW | 201311 | 1% | 86% | 12 |
8 | ELECTRICITY DEMAND | authKW | 147418 | 2% | 21% | 36 |
9 | SPATIAL LOAD FORECASTING | authKW | 137006 | 0% | 100% | 7 |
10 | LOAD PROFILING | authKW | 121945 | 1% | 69% | 9 |
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 | Energy & Fuels | 11751 | 28% | 0% | 438 |
2 | Engineering, Electrical & Electronic | 8556 | 44% | 0% | 682 |
3 | Computer Science, Artificial Intelligence | 4826 | 15% | 0% | 233 |
4 | Thermodynamics | 2446 | 11% | 0% | 166 |
5 | Operations Research & Management Science | 420 | 4% | 0% | 65 |
6 | Engineering, General | 401 | 4% | 0% | 68 |
7 | Environmental Studies | 344 | 3% | 0% | 46 |
8 | Automation & Control Systems | 239 | 3% | 0% | 46 |
9 | Management | 188 | 3% | 0% | 44 |
10 | Engineering, Chemical | 179 | 6% | 0% | 92 |
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 | BIGDEAL BIG DATA ENERGY ANALYT | 58717 | 0% | 100% | 3 |
2 | ENERGY ANALYT | 58717 | 0% | 100% | 3 |
3 | ENGN MATH SCI CECE | 58717 | 0% | 100% | 3 |
4 | GRP COMP NETWORKS SOFTWARE ENGN | 52190 | 0% | 67% | 4 |
5 | EXCELLENCE INTELLIGENT BASED EXPT MECH | 42077 | 1% | 13% | 16 |
6 | CENT LOAD DISPATCHING | 39144 | 0% | 100% | 2 |
7 | CHINA PROC OPTIMIZAT INTELLIGENT DECIS | 39144 | 0% | 100% | 2 |
8 | ENEA ENERGY ENVIRONM MODELLING TECH UNIT | 39144 | 0% | 100% | 2 |
9 | EREL | 39144 | 0% | 100% | 2 |
10 | ENERGY MANAGEMENT PLANNING | 37946 | 1% | 24% | 8 |
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 | IEEE TRANSACTIONS ON POWER SYSTEMS | 84508 | 12% | 2% | 181 |
2 | INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS | 39655 | 6% | 2% | 94 |
3 | ENGINEERING INTELLIGENT SYSTEMS FOR ELECTRICAL ENGINEERING AND COMMUNICATIONS | 36201 | 2% | 7% | 26 |
4 | ELECTRIC POWER SYSTEMS RESEARCH | 30946 | 5% | 2% | 84 |
5 | ENERGY | 19135 | 7% | 1% | 103 |
6 | ENERGY SOURCES PART B-ECONOMICS PLANNING AND POLICY | 15318 | 1% | 4% | 21 |
7 | IEE PROCEEDINGS-GENERATION TRANSMISSION AND DISTRIBUTION | 12833 | 2% | 2% | 29 |
8 | INTERNATIONAL JOURNAL OF FORECASTING | 11417 | 2% | 2% | 30 |
9 | ENERGIES | 9935 | 3% | 1% | 41 |
10 | APPLIED ENERGY | 7566 | 4% | 1% | 60 |
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 | SUGANTHI, L , SAMUEL, AA , (2012) ENERGY MODELS FOR DEMAND FORECASTING-A REVIEW.RENEWABLE & SUSTAINABLE ENERGY REVIEWS. VOL. 16. ISSUE 2. P. 1223 -1240 | 126 | 41% | 176 |
2 | HIPPERT, HS , PEDREIRA, CE , SOUZA, RC , (2001) NEURAL NETWORKS FOR SHORT-TERM LOAD FORECASTING: A REVIEW AND EVALUATION.IEEE TRANSACTIONS ON POWER SYSTEMS. VOL. 16. ISSUE 1. P. 44 -55 | 62 | 79% | 663 |
3 | ALFARES, HK , NAZEERUDDIN, M , (2002) ELECTRIC LOAD FORECASTING: LITERATURE SURVEY AND CLASSIFICATION OF METHODS.INTERNATIONAL JOURNAL OF SYSTEMS SCIENCE. VOL. 33. ISSUE 1. P. 23 -34 | 72 | 90% | 162 |
4 | HERNANDEZ, L , BALADRON, C , AGUIAR, JM , CARRO, B , SANCHEZ-ESGUEVILLAS, AJ , LLORET, J , MASSANA, J , (2014) A SURVEY ON ELECTRIC POWER DEMAND FORECASTING: FUTURE TRENDS IN SMART GRIDS, MICROGRIDS AND SMART BUILDINGS.IEEE COMMUNICATIONS SURVEYS AND TUTORIALS. VOL. 16. ISSUE 3. P. 1460 -1495 | 59 | 71% | 25 |
5 | KHUNTIA, SR , RUEDA, JL , VAN DER MEIJDEN, MAMM , (2016) FORECASTING THE LOAD OF ELECTRICAL POWER SYSTEMS IN MID- AND LONG-TERM HORIZONS: A REVIEW.IET GENERATION TRANSMISSION & DISTRIBUTION. VOL. 10. ISSUE 16. P. 3971 -3977 | 53 | 78% | 0 |
6 | HERNANDEZ, L , BALADRON, C , AGUIAR, JM , CARRO, B , SANCHEZ-ESGUEVILLAS, AJ , LLORET, J , (2013) SHORT-TERM LOAD FORECASTING FOR MICROGRIDS BASED ON ARTIFICIAL NEURAL NETWORKS.ENERGIES. VOL. 6. ISSUE 3. P. 1385-1408 | 45 | 82% | 25 |
7 | LAHOUAR, A , SLAMA, JH , (2015) DAY-AHEAD LOAD FORECAST USING RANDOM FOREST AND EXPERT INPUT SELECTION.ENERGY CONVERSION AND MANAGEMENT. VOL. 103. ISSUE . P. 1040 -1051 | 37 | 93% | 8 |
8 | LIN, CT , CHOU, LD , CHEN, YM , TSENG, LM , (2014) A HYBRID ECONOMIC INDICES BASED SHORT-TERM LOAD FORECASTING SYSTEM.INTERNATIONAL JOURNAL OF ELECTRICAL POWER & ENERGY SYSTEMS. VOL. 54. ISSUE . P. 293-305 | 41 | 91% | 6 |
9 | HONG, T , FAN, S , (2016) PROBABILISTIC ELECTRIC LOAD FORECASTING: A TUTORIAL REVIEW.INTERNATIONAL JOURNAL OF FORECASTING. VOL. 32. ISSUE 3. P. 914 -938 | 44 | 70% | 2 |
10 | NAGI, J , YAP, KS , NAGI, F , TIONG, SK , AHMED, SK , (2011) A COMPUTATIONAL INTELLIGENCE SCHEME FOR THE PREDICTION OF THE DAILY PEAK LOAD.APPLIED SOFT COMPUTING. VOL. 11. ISSUE 8. P. 4773 -4788 | 52 | 64% | 31 |
Classes with closest relation at Level 1 |