2003 - Fellow of the Royal Academy of Engineering (UK)
Derek A. Linkens mostly deals with Fuzzy logic, Fuzzy control system, Artificial intelligence, Neuro-fuzzy and Control theory. His Fuzzy logic research incorporates elements of Artificial neural network, Control and Control theory. The concepts of his Fuzzy control system study are interwoven with issues in Intelligent control, Adaptive control, Intensive care and Pendulum.
His study in the fields of Expert system under the domain of Artificial intelligence overlaps with other disciplines such as Microarray analysis techniques. His Neuro-fuzzy research incorporates elements of Intelligent decision support system, Defuzzification and Fuzzy clustering. His Multivariable calculus and Limit cycle study in the realm of Control theory connects with subjects such as Relaxation oscillator and Ring.
His primary scientific interests are in Fuzzy logic, Artificial intelligence, Control theory, Fuzzy control system and Artificial neural network. His Fuzzy logic study combines topics from a wide range of disciplines, such as Control engineering, Control system and Control. His research in Artificial intelligence intersects with topics in Genetic algorithm and Machine learning.
Robustness and Feed forward is closely connected to Model predictive control in his research, which is encompassed under the umbrella topic of Control theory. Much of his study explores Fuzzy control system relationship to Intelligent control. His studies in Artificial neural network integrate themes in fields like Bladder cancer and Algorithm.
Derek A. Linkens spends much of his time researching Artificial intelligence, Fuzzy logic, Bladder cancer, Finite element method and Metallurgy. In general Artificial intelligence, his work in Adaptive neuro fuzzy inference system, Fuzzy control system and Artificial neural network is often linked to Microarray analysis techniques linking many areas of study. His study looks at the relationship between Adaptive neuro fuzzy inference system and fields such as Fuzzy classification, as well as how they intersect with chemical problems.
As part of the same scientific family, Derek A. Linkens usually focuses on Fuzzy logic, concentrating on Control engineering and intersecting with Real-time computing, Process and Control. His Bladder cancer research includes elements of Tumor progression, Disease, Oncology and Cohort. His study in Finite element method is interdisciplinary in nature, drawing from both Mechanical engineering, Mechanics, Aluminium and Cellular automaton.
His scientific interests lie mostly in Artificial intelligence, Flow stress, Plane stress, Tumor progression and Cancer. His is involved in several facets of Artificial intelligence study, as is seen by his studies on Marketing and artificial intelligence, Artificial neural network, Data-driven, Expert system and Bayesian network. His biological study spans a wide range of topics, including Stress relaxation, Stress and Stress intensity factor.
His work deals with themes such as Odds ratio and Multivariate analysis, which intersect with Tumor progression. Derek A. Linkens studied Cancer and Risk factor that intersect with Oncology and Bladder cancer. The various areas that he examines in his Finite element method study include Deformation, Neuro-fuzzy, Algorithm, Cellular automaton and Material Design.
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Genetic algorithms for fuzzy control.1. Offline system development and application
D.A. Linkens;H.O. Nyongesa.
IEE Proceedings - Control Theory and Applications (1995)
Genetic algorithms for fuzzy control.1. Offline system development and application
D.A. Linkens;H.O. Nyongesa.
IEE Proceedings - Control Theory and Applications (1995)
Survey of utilisation of fuzzy technology in medicine and healthcare
Maysam F. Abbod;Diedrich G. von Keyserlingk;Derek A. Linkens;Mahdi Mahfouf.
Fuzzy Sets and Systems (2001)
Survey of utilisation of fuzzy technology in medicine and healthcare
Maysam F. Abbod;Diedrich G. von Keyserlingk;Derek A. Linkens;Mahdi Mahfouf.
Fuzzy Sets and Systems (2001)
Rule-base self-generation and simplification for data-driven fuzzy models
Min-You Chen;Derek A. Linkens.
Fuzzy Sets and Systems (2004)
Rule-base self-generation and simplification for data-driven fuzzy models
Min-You Chen;Derek A. Linkens.
Fuzzy Sets and Systems (2004)
Learning systems in intelligent control: an appraisal of fuzzy, neural and genetic algorithm control applications
D.A. Linkens;H.O. Nyongesa.
IEE Proceedings - Control Theory and Applications (1996)
Learning systems in intelligent control: an appraisal of fuzzy, neural and genetic algorithm control applications
D.A. Linkens;H.O. Nyongesa.
IEE Proceedings - Control Theory and Applications (1996)
Promoter Hypermethylation Identifies Progression Risk in Bladder Cancer
Yates;I Rehman;M F Abbod;M Meuth.
Clinical Cancer Research (2007)
A survey of fuzzy logic monitoring and control utilisation in medicine
M Mahfouf;M.F Abbod;D.A Linkens.
Artificial Intelligence in Medicine (2001)
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