Natural Computing Research Papers - Academia.edu (original) (raw)

Combining forecasts is a common practice in time series analysis. This technique involves weighing each estimate of different models in order to minimize the error between the resulting output and the target. This work presents a novel... more

Combining forecasts is a common practice in time series analysis. This technique involves weighing each estimate of different models in order to minimize the error between the resulting output and the target. This work presents a novel methodology, aiming to combine forecasts using genetic programming, a metaheuristic that searches for a nonlinear combination and selection of forecasters simultaneously. To present the method, the authors made three different tests comparing with the linear forecasting combination, evaluating both in terms of RMSE and MAPE. The statistical analysis shows that the genetic programming combination outperforms the linear combination in two of the three tests evaluated.

In this statement we provide some examples of transdisciplinaryjourneys, from one field to another, and back. In particular, thequantuminformaticendeavoris not just a matter of feedingphys-ical theory into the general field of natural... more

In this statement we provide some examples of transdisciplinaryjourneys, from one field to another, and back. In particular, thequantuminformaticendeavoris not just a matter of feedingphys-ical theory into the general field of natural computation, bu t alsoone of using high-level methods developed in Computer Scienceto improve on the quantum physical formalism itself, and theunderstanding thereof. We highlight a seemingly contradictoryphenomenon: passing to an abstract, categorical quantum infor-matic formalism leads directly to a simple and elegant graphicalformulation of quantum theory itself, which for example makesthe design of some importantquantuminformaticprotocolscom-pletely transparent. It turns out that essentially all of the quan-tum informatic machinery can be recovered from this graphicalcalculus. But in turn, this graphical formalism provides a bridgebetween methods of logic and computer science, and some of themost exciting developments in the mathematics of the past tw...

We define a new relation on words by a finite series of insertions and/or deletions of palindromic subwords. In particular we concentrate on insertion or deletion of Watson–Crick palindromes. We show that the new relation ∼θ is, in fact,... more

We define a new relation on words by a finite series of insertions and/or deletions of palindromic subwords. In particular we concentrate on insertion or deletion of Watson–Crick palindromes. We show that the new relation ∼θ is, in fact, an equivalence relation where θ is any arbitrary antimorphic involution that is not the identity on the letters of the alphabet. We also show that the set of all θ-palindromic free words defined in (Daley et al. in preparation) is ∼θ-independent. Using the relation we define a new subclass of primitive words which we call as ∼θ-primitive words and show that the class of all ∼θ-primitive words is closed under circular permutations. We also define ∼θ-conjugates and ∼θ-commutativity and study the properties of such words and show that they are similar to that of conjugate words and words that commute.

The world of finance is an exciting and challenging environment. Recent years have seen an explosion in the application of computational intelligence methodologies in finance. In this article we provide an overview of some of these... more

The world of finance is an exciting and challenging environment. Recent years have seen an explosion in the application of computational intelligence methodologies in finance. In this article we provide an overview of some of these applications concentrating on those employing an evolutionary computation approach.

This paper proposes a multiobjective formulation for variable selection in multivariate calibration problems in order to improve the generalization ability of the calibration model. The authors applied this proposed formulation in the... more

This paper proposes a multiobjective formulation for variable selection in multivariate calibration problems in order to improve the generalization ability of the calibration model. The authors applied this proposed formulation in the multiobjective genetic algorithm NSGA-II. The formulation consists in two conflicting objectives: minimize the prediction error and minimize the number of selected variables for multiple linear regression. These objectives are conflicting because, when the number of variables is reduced the prediction error increases. As study of case is used the wheat data set obtained by NIR spectrometry with the objective for determining a variable subgroup with information about protein concentration. The results of traditional techniques of multivariate calibration as the partial least square and successive projection algorithm for multiple linear regression are presented for comparisons. The obtained results showed that the proposed approach obtained better resul...

The growing complexity of real-world problems has motivated computer scientists to search for efficient problem-solving methods. Evolutionary Computation and Swarm Intelligence metaheuristics are outstanding examples that nature has been... more

The growing complexity of real-world problems has motivated computer scientists to search for efficient problem-solving methods. Evolutionary Computation and Swarm Intelligence metaheuristics are outstanding examples that nature has been an unending source of inspiration. The behavior of bees, bacteria, glowworms, fireflies, slime molds, cockroaches, mosquitoes and other organisms have inspired swarm intelligence researchers to devise new optimization algorithms. This tutorial highlights the most recent nature-based inspirations as metaphors for swarm intelligence metaheuristics. We describe the biological behaviors from which a number of computational algorithms were developed. Also, the most recent and important applications and the main features of such metaheuristics are reported.

We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve... more

We view Digital Ecosystems to be the digital counterparts of biological ecosystems. Here, we are concerned with the creation of these Digital Ecosystems, exploiting the self-organising properties of biological ecosystems to evolve high-level software applications. Therefore, we created the Digital Ecosystem, a novel optimisation technique inspired by biological ecosystems, where the optimisation works at two levels: a first optimisation, migration of agents which are distributed in a decentralised peer-to-peer network, operating continuously in time; this process feeds a second optimisation based on evolutionary computing that operates locally on single peers and is aimed at finding solutions to satisfy locally relevant constraints. The Digital Ecosystem was then measured experimentally through simulations, with measures originating from theoretical ecology, evaluating its likeness to biological ecosystems. This included its responsiveness to requests for applications from the user base, as a measure of the ecological succession (ecosystem maturity). Overall, we have advanced the understanding of Digital Ecosystems, creating Ecosystem-Oriented Architectures (EOA) where the word ecosystem is more than just a metaphor.

[CLICK ON PAPER TITLE, THEN ON "READ PAPER" AT BOTTOM OF SCREEN] In the first of two papers on MAGMA, a new system for computational algebra, we present the MAGMA language, outline the design principles and theoretical background, and... more

[CLICK ON PAPER TITLE, THEN ON "READ PAPER" AT BOTTOM OF SCREEN] In the first of two papers on MAGMA, a new system for computational algebra, we present the MAGMA language, outline the design principles and theoretical background, and indicate its scope and use. Particular attention is given to the constructors for structures, maps, and sets. [co-authors Wieb Bosma and John Cannon, not on Academia.edu]

This paper proposes a multiobjective formulation for variable selection in multivariate calibration problems in order to improve the generalization ability of the calibration model. The authors applied this proposed formulation in the... more

This paper proposes a multiobjective formulation for variable selection in multivariate calibration problems in order to improve the generalization ability of the calibration model. The authors applied this proposed formulation in the multiobjective genetic algorithm NSGA-II. The formulation consists in two conflicting objectives: minimize the prediction error and minimize the number of selected variables for multiple linear regression. These objectives are conflicting because, when the number of variables is reduced the prediction error increases. As study of case is used the wheat data set obtained by NIR spectrometry with the objective for determining a variable subgroup with information about protein concentration. The results of traditional techniques of multivariate calibration as the partial least square and successive projection algorithm for multiple linear regression are presented for comparisons. The obtained results showed that the proposed approach obtained better resul...

Bat Algorithm (BA) is a simple and effective global optimization algorithm which has been applied to a wide range of real-world optimisation problems. Various extensions to Bat algorithm have been proposed in the past; prominent amongst... more

Bat Algorithm (BA) is a simple and effective global optimization algorithm which has been applied to a wide range of real-world optimisation problems. Various extensions to Bat algorithm have been proposed in the past; prominent amongst them being ShBAT. ShBAT is a hybrid between BA and Shuffled Frog Leaping Algorithm-SFLA; a memetic algorithm based on food search behavior of frogs. ShBAT integrates the shuffling and reorganization technique of SFLA to enhance the exploitation capabilities of BAT. This paper proposes Enhanced Shuffled Bat algorithm (EShBAT) an extension to ShBAT. In ShBAT, different memeplexes evolve independently, with different cultures. EShBAT improves the exploitation capabilities of ShBAT by grouping together the best of each memeplex to form a super-memeplex. This super-memeplex evolves independently to further exploit the best solutions. The performance of EShBAT is verified over 30 well-known benchmark functions. Experimental results indicate a significant improvement of EShBAT over BA and ShBAT.

To date, a number of researchers are seeking for and/or designing novel molecules which function as arithmetic molecular engines. Biomolecules such as deoxyribonucleic acid (DNA) and proteins are examples of promising candidate molecules.... more

To date, a number of researchers are seeking for and/or designing novel molecules which function as arithmetic molecular engines. Biomolecules such as deoxyribonucleic acid (DNA) and proteins are examples of promising candidate molecules. In the present article, we showed our view that DNA-based molecules could be used as a novel class of platforms for discrete mathematical operations or tools for natural computation. Here, we report on a novel molecular logic circuit combining exclusive disjunction (XOR) gate and conjunction (AND) gate implemented on a single DNA molecule performing arithmetic operations with simple binary numbers through polymerase chain reactions (PCR); which was inspired by previously developed protein-based computing model allowing simple polynomial algebra over fields through algebraic representation of cyclic inter-conversions in the catalytic modes of a plant enzyme as a cyclic additive group. In addition, we showed that DNA can be used as the platform for image coding and processing leading to DNA-coded animation by using novel PCR-based protocols. Lastly, we discussed the significance of recent attempts in the stream of natural computing and synthetic biological research, by handling DNA and related biomolecules as the media for discrete mathematical operations.

This paper reports the hybridization of the artificial bee colony (ABC) and a genetic algorithm (GA), ina hierarchical topology, a step ahead of a previous work. We used this parallel approach for solving theprotein structure prediction... more

This paper reports the hybridization of the artificial bee colony (ABC) and a genetic algorithm (GA), ina hierarchical topology, a step ahead of a previous work. We used this parallel approach for solving theprotein structure prediction problem using the three-dimensional hydrophobic-polar model with side-chains(3DHP-SC). The proposed method was run in a parallel processing environment (Beowulf cluster), andseveral aspects of the modeling and implementation are presented and discussed. The performance of thehybrid-hierarchical ABC-GA approach was compared with a hybrid-hierarchical ABC-only approach forfour benchmark instances. Results show that the hybridization of the ABC with the GA improves the qualityof solutions caused by the coevolution effect between them and their search behavior. Copyright © 2011John Wiley & Sons, Ltd.

The capability to establish adaptive relationships with the environment is an essential characteristic of living cells. Both bacterial computing and bacterial intelligence are two general traits manifested along adaptive behaviors that... more

The capability to establish adaptive relationships with the environment is an essential characteristic of living cells. Both bacterial computing and bacterial intelligence are two general traits manifested along adaptive behaviors that respond to surrounding environmental conditions. These two traits have generated a variety of theoretical and applied approaches. Since the different systems of bacterial signaling and the different ways of genetic change are better known and more carefully explored, the whole adaptive possibilities of bacteria may be studied under new angles. For instance, there appear instances of molecular "learning" along the mechanisms of evolution. More in concrete, and looking specifically at the time dimension, the bacterial mechanisms of learning and evolution appear as two different and related mechanisms for adaptation to the environment; in somatic time the former and in evolutionary time the latter. In the present chapter it will be reviewed the...

When noise dominates an information system, like in nano-electronic systems of the foreseeable future, a natural question occurs: Can we perhaps utilize the noise as information carrier? Another question is: Can a deterministic logic... more

When noise dominates an information system, like in nano-electronic systems of the foreseeable future, a natural question occurs: Can we perhaps utilize the noise as information carrier? Another question is: Can a deterministic logic scheme be constructed that may explain how the brain efficiently processes information, with random neural spike trains of less than 100 Hz frequency, and with a similar number of human brain neurons as the number of transistors in a 16 GB Flash dive? The answers to these questions are yes. Related developments indicate reduced power consumption with noise-based deterministic Boolean logic gates and the more powerful multivalued logic versions with an arbitrary number of logic values. Similar schemes as the Hilbert space of quantum informatics can also be constructed with noise-based logic by utilizing the noise-bits and their multidimensional hyperspace without the limitations of quantum-collapse of wavefunctions. A noise-based string search algorithm faster than Grover’s quantum search algorithm can be obtained, with the same hardware complexity class as the quantum engine. This logic hyperspace scheme has also been utilized to construct the noise-based neuro-bits and a deterministic multivalued logic scheme for the brain. Some of the corresponding circuitry of neurons is shown. Some questions and answers about a chip realization of such a random spike based deterministic multivalued logic scheme are presented.

Today's software applications increasingly feature a great deal of openness, dynamism and unpredictable behav- ior, forcing to shift design and engineering from traditional, centralized approaches to nature-inspired, self-organizing... more

Today's software applications increasingly feature a great deal of openness, dynamism and unpredictable behav- ior, forcing to shift design and engineering from traditional, centralized approaches to nature-inspired, self-organizing tech- niques. Among the others, biology has been adopted as a source of inspiration to solve some of the issues proper of nowadays systems by self-organizing techniques, usually exploited in an ad-hoc