Results 131 to 140 of about 11,497,181 (207)

Machine learning and evolutionary techniques in interplanetary trajectory design

Springer Optimization and Its Applications, 2018
After providing a brief historical overview on the synergies between artificial intelligence research, in the areas of evolutionary computations and machine learning, and the optimal design of interplanetary trajectories, we propose and study the use of ...
D. Izzo, Christopher Iliffe Sprague, D. Tailor   +2 more
semanticscholar   +1 more source

Evolutionary Techniques in MEMS Synthesis

Volume 1A: 25th Biennial Mechanisms Conference, 1998
Abstract Initial results have been obtained for automatic synthesis of MEMS mask-layouts using a genetic algorithm. An initial random population of geometrically valid mask-layouts (non-self intersecting 2D polygons) is produced. The fabrication of each layout is simulated using a 3-D simulation of etching.
Hui Li, Erik K. Antonsson
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Evolutionary Techniques for Automation

2009
In this chapter, evolutionary techniques (ETs) will be introduced for treating automation problems in factory, manufacturing, planning and scheduling, and logistics and transportation systems. ET is the most popular metaheuristic method for solving NP-hard optimization problems.
Mitsuo Gen, Lin Lin
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Evolutionary techniques for fault tolerance

UKACC International Conference on Control. Control '96, 1996
Artificial evolution can integrate fault tolerance considerations into the automatic design process, producing inherently fault-tolerant designs without explicit redundant parts. Population dynamics can give rise to some level of fault tolerance `for free'. Requirements for fault tolerance can also be incorporated into the fitness function.
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Evolutionary computational techniques in electromagnetics

International Conference on Mathematical Methods in Electromagnetic Theory, 2003
The three paradigms of the evolutionary algorithms, namely, Genetic Algorithms, Evolution Strategies and Evolutionary Programming, are briefly reviewed, and the applications of the latter to optimizations of continuous as well as mixed parameter electromagnetic problems are discussed in details.
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ISSR Techniques for Evolutionary Biology

2005
Inter-simple sequence repeat (ISSR) markers were originally devised for differentiating among closely related plant cultivars but have become extremely useful for studies of natural populations of plants, fungi, insects, and vertebrates. The markers are easily generated using minimal equipment and are hypervariable, yielding a large amount of data for ...
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Optimization Techniques and Evolutionary Algorithms

2021
The field of artificial intelligence (AI) continues to evolve at an extraordinary pace, and at the heart of many AI breakthroughs lies the discipline of opti- mization. This book, Optimization Techniques and Evolutionary Algorithms, was written to address the growing need for a clear and practical introduction to optimization, especially as it applies ...
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Portfolio Selection Using Evolutionary Computational Techniques

SSRN Electronic Journal, 2007
We present in this paper a new approach to portfolio selection using imprecise model, Fuzzy goal programming and Genetic algorithm. The results of this approach is compared with traditional portfolio selection and presented here. In conventional methods, the skewness of portfolio returns is not considered.
Ishu Bhansal, Dr. S. Srinivasan
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Evolutionary Testing Techniques

2005
The development and testing of software-based systems is an essential activity for the automotive industry. 50-70 software-based systems with different complexities and developed by various suppliers are installed in today's premium vehicles, communicating with each other via different bus systems.
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Effective Classification with Hybrid Evolutionary Techniques

2006 International Conference on Advanced Computing and Communications, 2006
Ant colony optimization (ACO) algorithms have been applied successfully to combinatorial optimization problems. More recently, Parpinelli et al have applied ACO to data mining classification problems, where they introduced a classification algorithm called Ant Miner.
P. Jaganathan, A. K. Thangavel, A. Pethalakshmi   +2 more
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