In this work we show an innovative approach to the protein folding problem based on an hybrid Immune Algorithm (IA) and a quasi-Newton method starting from a population of promising protein conformations created by th...
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ISBN:
(纸本)3540331832
In this work we show an innovative approach to the protein folding problem based on an hybrid Immune Algorithm (IA) and a quasi-Newton method starting from a population of promising protein conformations created by the global optimizer DIRECT. The new method has been tested on Met-Enkephelin peptide, which is a paradigmatic example of multiple-minima problem, 1POLY, 1ROP and the three helix protein 1BDC. The experimental results show as the multistage approach is a competitive and effective search method in the conformational search space of real proteins, in terms of quality solution and computational cost comparing the results of the current state-of-art algorithms.
We present an Immune Algorithm (IA) based on clonalselection principle and which uses memory B cells, to face the protein structure prediction problem (PSP) a particular example of the String Folding Problem in 21) a...
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ISBN:
(纸本)3540253378
We present an Immune Algorithm (IA) based on clonalselection principle and which uses memory B cells, to face the protein structure prediction problem (PSP) a particular example of the String Folding Problem in 21) and 3D lattice. Memory B cells with a longer life span are used to partition the funnel landscape of PSP, so to properly explore the search space. The designed IA shows its ability to tackle standard benchmarks instances substantially better than other IA's. In particular, for the 3D HP model the IA allowed us to find energy minima not found by other evolutionary algorithms described in literature.
There are different theories and models in natural immune system, so computer science researchers have created various algorithms to simulate processes of immune system, such as immune network based models, negative s...
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ISBN:
(纸本)9781479956043
There are different theories and models in natural immune system, so computer science researchers have created various algorithms to simulate processes of immune system, such as immune network based models, negative selection, and clonalselection. In this paper a novel dynamic clonalselection algorithm has been used to solve File Transfer Scheduling optimization problem. In proposed algorithm, the parameters of clonalselection algorithm will be changed over generations with hope of decreasing run-time, and at the same time the performance of the algorithm remains at an acceptable level. Then after some generations a population control strategy handles the size of antibody population. Antibodies have been created such that, the degree of simultaneous sending of files be maximized for a given transfer sequence of files. This causes make-span of schedule be minimized for that sequence. The proposed algorithm has been examined on these problems with different sizes. The results of experiments show that, the rate of reaching to global optimum is acceptable.
Natural immune system has features such as pattern recognition, diversity, learning, distributed detection, stochastic detection, and adaptability, that make it a great metaphor to solve hard problems. In two last dec...
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ISBN:
(纸本)9780769550053
Natural immune system has features such as pattern recognition, diversity, learning, distributed detection, stochastic detection, and adaptability, that make it a great metaphor to solve hard problems. In two last decades artificial immune systems, as a novel computational artificial intelligence approach, are used to solve hard optimization problems. As for existence of different theories and models in theoretical immunity society, researchers have created various algorithms to simulate processes of immune system, such as immune network based models, negative selection, clonalselection. In this paper a clonalselection algorithm have been used to solve File Transfer Scheduling optimization problem. In proposed approach, antibodies have been created such that, the degree of simultaneous sending of files be maximized for a given transfer sequence of files, this cause make-span of schedule be minimized for that sequence. The proposed algorithm have been examined on this problem with different size, the result of experiments shown that, reaching global optimum rate of the algorithm are acceptable. Also a population control strategy is used to reduce the run time of algorithm.
In this paper, an important class of hypermutation operators axe discussed and quantitatively compared with respect to their success rate and computational cost. We use a standard Immune Algorithm (IA), based on the c...
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ISBN:
(纸本)3540230971
In this paper, an important class of hypermutation operators axe discussed and quantitatively compared with respect to their success rate and computational cost. We use a standard Immune Algorithm (IA), based on the clonalselection principle to investigate the searching capability of the designed hypermutation operators. We computed the parameter surface for each variation operator to predict the best parameter setting for each operator and their combination. The experimental investigation in which we use a standard clonalselection algorithm with different hypermutation operators on a complex "toy problem", the trap functions, and a complex NP-complete problem, the 2D HP model for the protein structure prediction problem, clarifies that only few really different and useful hypermutation operators exist, namely: inversely proportional hypermutation, static hypermutation and hypermacromutation operators. The combination of static and inversely proportional Hypermutation and hypermacromutation showed the best experimental results for the "toy problem" and the NP-complete problem.
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