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Results: 1-16 |
Results: 16
CERTAINTY FACTORS VERSUS PARZEN WINDOWS AS RELIABILITY-MEASURES IN RBF NETWORKS
Authors: WEDDING DK CIOS KJ
Citation: Dk. Wedding et Kj. Cios, CERTAINTY FACTORS VERSUS PARZEN WINDOWS AS RELIABILITY-MEASURES IN RBF NETWORKS, Neurocomputing, 19(1-3), 1998, pp. 151-165
NEURAL-NETWORKS-BASED ADAPTIVE-CONTROL OF FLEXIBLE ROBOTIC ARMS
Authors: ARCINIEGAS JI ELTIMSAHY AH CIOS KJ
Citation: Ji. Arciniegas et al., NEURAL-NETWORKS-BASED ADAPTIVE-CONTROL OF FLEXIBLE ROBOTIC ARMS, Neurocomputing, 17(3-4), 1997, pp. 141-157
ONTOGENIC NEURO-FUZZY ALGORITHM - F-CID3
Authors: CIOS KJ SZTANDERA LM
Citation: Kj. Cios et Lm. Sztandera, ONTOGENIC NEURO-FUZZY ALGORITHM - F-CID3, Neurocomputing, 14(4), 1997, pp. 383-402
IDENTIFYING CORONARY STENOSIS USING AN IMAGE-RECOGNITION NEURAL-NETWORK
Authors: GOODENDAY LS CIOS KJ SHIN IH
Citation: Ls. Goodenday et al., IDENTIFYING CORONARY STENOSIS USING AN IMAGE-RECOGNITION NEURAL-NETWORK, IEEE engineering in medicine and biology magazine, 16(5), 1997, pp. 139-144
CLIP3 - COVER LEARNING USING INTEGER PROGRAMMING
Authors: CIOS KJ WEDDING DK LIU N
Citation: Kj. Cios et al., CLIP3 - COVER LEARNING USING INTEGER PROGRAMMING, Kybernetes, 26(4-5), 1997, pp. 513
TIME-SERIES FORECASTING BY COMBINING RBF NETWORKS, CERTAINTY FACTORS,AND THE BOX-JENKINS MODEL
Authors: WEDDING DK CIOS KJ
Citation: Dk. Wedding et Kj. Cios, TIME-SERIES FORECASTING BY COMBINING RBF NETWORKS, CERTAINTY FACTORS,AND THE BOX-JENKINS MODEL, Neurocomputing, 10(2), 1996, pp. 149-168
INDUCTIVE MACHINE LEARNING FOR INSTRUMENT DEVELOPMENT
Authors: TORKZADEH G CIOS KJ PFLUGHOEFT KA
Citation: G. Torkzadeh et al., INDUCTIVE MACHINE LEARNING FOR INSTRUMENT DEVELOPMENT, Information & management, 31(1), 1996, pp. 47-55
A NEURO-FUZZY ALGORITHM FOR DIAGNOSIS OF CORONARY-ARTERY STENOSIS
Authors: SZTANDERA LM GOODENDAY LS CIOS KJ
Citation: Lm. Sztandera et al., A NEURO-FUZZY ALGORITHM FOR DIAGNOSIS OF CORONARY-ARTERY STENOSIS, Computers in biology and medicine, 26(2), 1996, pp. 97-111
IMAGE RECOGNITION NEURAL-NETWORK - IRNN
Authors: CIOS KJ SHIN I
Citation: Kj. Cios et I. Shin, IMAGE RECOGNITION NEURAL-NETWORK - IRNN, Neurocomputing, 7(2), 1995, pp. 159-185
SOFT COMPUTING IN DESIGN AND MANUFACTURING OF ADVANCED MATERIALS
Authors: CIOS KJ BAAKLINI GY VARY A
Citation: Kj. Cios et al., SOFT COMPUTING IN DESIGN AND MANUFACTURING OF ADVANCED MATERIALS, Journal of engineering for gas turbines and power, 117(1), 1995, pp. 161-165
AN ALGORITHM WHICH LEARNS MULTIPLE COVERS VIA INTEGER LINEAR-PROGRAMMING .2. EXPERIMENTAL RESULTS AND CONCLUSIONS
Authors: CIOS KJ LIU N
Citation: Kj. Cios et N. Liu, AN ALGORITHM WHICH LEARNS MULTIPLE COVERS VIA INTEGER LINEAR-PROGRAMMING .2. EXPERIMENTAL RESULTS AND CONCLUSIONS, Kybernetes, 24(3), 1995, pp. 24
AN ALGORITHM WHICH LEARNS MULTIPLE COVERS VIA INTEGER LINEAR-PROGRAMMING .1. THE CLILP2 ALGORITHM
Authors: CIOS KJ LIU N
Citation: Kj. Cios et N. Liu, AN ALGORITHM WHICH LEARNS MULTIPLE COVERS VIA INTEGER LINEAR-PROGRAMMING .1. THE CLILP2 ALGORITHM, Kybernetes, 24(2), 1995, pp. 29-50
HYBRID INTELLIGENCE SYSTEMS FOR DIAGNOSING CORONARY STENOSIS
Authors: CIOS KJ GOODENDAY LS SZTANDERA LM
Citation: Kj. Cios et al., HYBRID INTELLIGENCE SYSTEMS FOR DIAGNOSING CORONARY STENOSIS, IEEE engineering in medicine and biology magazine, 13(5), 1994, pp. 723-729
RADIAL BASIS FUNCTION NETWORK LEARNS CERAMIC PROCESSING AND PREDICTS RELATED STRENGTH AND DENSITY
Authors: CIOS KJ BAAKLINI GY VARY A TJIA RE
Citation: Kj. Cios et al., RADIAL BASIS FUNCTION NETWORK LEARNS CERAMIC PROCESSING AND PREDICTS RELATED STRENGTH AND DENSITY, Journal of testing and evaluation, 22(4), 1994, pp. 343-350
USING FUZZY-SETS IN THE PREDICTION OF FLEXURAL STRENGTH AND DENSITY OF SILICON-NITRIDE CERAMICS
Authors: CIOS KJ BAAKLINI GY VARY A SZTANDERA LM
Citation: Kj. Cios et al., USING FUZZY-SETS IN THE PREDICTION OF FLEXURAL STRENGTH AND DENSITY OF SILICON-NITRIDE CERAMICS, Materials evaluation, 52(5), 1994, pp. 600-606
GENERATION OF DIAGNOSTIC RULES VIA INDUCTIVE MACHINE LEARNING
Authors: CIOS KJ LIU N GOODENDAY LS
Citation: Kj. Cios et al., GENERATION OF DIAGNOSTIC RULES VIA INDUCTIVE MACHINE LEARNING, Kybernetes, 22(5), 1993, pp. 44-56
Risultati: 1-16 |