scholarly journals Heuristic Strategies as a Toolbox in Complex Modelling Problems

Author(s):  
Peter Stender
Author(s):  
Carlos Ortiz de Landázuri

Heidegger, Zubiri, Apel y Polo habrían propuesto una definición más correcta de las respectivas nociones de sujeto relacional humano, a saber: “Dasein” o “ser-ahí”; “personeidad” o “esencia abierta”; “intersubjetividad” o “la llamada por parte de los entes a diversos interlocutores”; y, finalmente, “persona-núcleo” o “agente mediador entre los entes y el ser”. Se pretendía así evitar una vuelta a las paradojas del “sujeto transcendental” en Kant, del “yo absoluto” en Hegel o del “sujeto fenomenológico” en Husserl. Sin embargo en cada caso se siguieron estrategias heurísticas específicamente distintas a la hora de conceptualizar dicho sujeto relacional: Heidegger propuso una superación de la noción de “sujeto fenomenológico” en Husserl; Zubiri, en cambio, defendería una recuperación de la noción de “sujeto fenomenológico” en Husserl; por su parte, Apel propondría una reformulación semióticamente transformada del “Dasein” heideggeriano; finalmente, Polo propondría una reformulación gnoseológica de la noción de “Dasein” heideggeriano.Heidegger, Zubiri, Apel, and Polo have proposed a more accurate definition of the respective notions of human relational subject: “Dasein” or “being-there”; “Personhood” or “open essence”; “inter-subjectivity” or “entities’ appeal to diverse interlocutors”; and, finally, “nucleus-person” or “mediator between entities and being”. The aim is to avoid a return to Kant’s transcendental subject paradoxes and Hegel’s “absolute I” or Husserl´s “fenomenological subject”. But in each case specifically different heuristic strategies were followed when conceptualizing said relational subject: Heidegger proposed overcoming the notion of “phenomenological subject” in Husserl; Zubiri, however, defend the recovery of the notion of “phenomenological subject” in Husserl; meanwhile, Apel propose a transformed semiotically reformulation of Heidegger’s “Dasein”; finally, Polo propose a reformulation of the epistemological notion of Heidegger’s “Dasein”.


2005 ◽  
Vol 6 (1) ◽  
pp. 41-55 ◽  
Author(s):  
Miguel A. Herrero ◽  
José M. López

In this work we succintly review the main features of bone formation in vertebrates. Out of the many aspects of this exceedingly complex process, some particular stages are selected for which mathematical modelling appears as both feasible and desirable. In this way, a number of open questions are formulated whose study seems to require interaction among mathematical analysis and biological experimentation.


2020 ◽  
Vol 51 (3) ◽  
pp. 01-03
Author(s):  
Christin Braun

Groundwater asset the executives is a difficult issue looked by practically all the nations. Numerical models of these issues frequently end up being not well characterized subject to a few factors and requirements. This examination is centred on the variety of physico-substance boundaries in water tests undergone with 2 unique destinations. The Dissolved Oxygen substance and Total Dissolved Solids substance of a large portion of the examples are past as far as possible. The chloride satisfied close to the dump-site is seen as extremely high contrasted with the non-dirtied site. Refined calculations are required so as to manage such issues. In the consideration has been paid to heuristic strategies like hereditary calculations and so on which can undoubtedly take care of such issues. Further, so as to handle the enormous number of included boundaries in these issues equal form of GAs is more successful than the fundamental gallium. In this magazine, an endeavour is finished to audit the use of equal variant of GA on groundwater contamination issues.


Symmetry ◽  
2019 ◽  
Vol 11 (9) ◽  
pp. 1142
Author(s):  
Feng Cao ◽  
Yang Xu ◽  
Jun Liu ◽  
Shuwei Chen ◽  
Xinran Ning

First-order logic is an important part of mathematical logic, and automated theorem proving is an interdisciplinary field of mathematics and computer science. The paper presents an automated theorem prover for first-order logic, called C S E _ E 1.0, which is a combination of two provers contradiction separation extension (CSE) and E, where CSE is based on the recently-introduced multi-clause standard contradiction separation (S-CS) calculus for first-order logic and E is the well-known equational theorem prover for first-order logic based on superposition and rewriting. The motivation of the combined prover C S E _ E 1.0 is to (1) evaluate the capability, applicability and generality of C S E _ E , and (2) take advantage of novel multi-clause S-CS dynamic deduction of CSE and mature equality handling of E to solve more and harder problems. In contrast to other improvements of E, C S E _ E 1.0 optimizes E mainly from the inference mechanism aspect. The focus of the present work is given to the description of C S E _ E including its S-CS rule, heuristic strategies, and the S-CS dynamic deduction algorithm for implementation. In terms of combination, in order not to lose the capability of E and use C S E _ E to solve some hard problems which are unsolved by E, C S E _ E 1.0 schedules the running of the two provers in time. It runs plain E first, and if E does not find a proof, it runs plain CSE, then if it does not find a proof, some clauses inferred in the CSE run as lemmas are added to the original clause set and the combined clause set handed back to E for further proof search. C S E _ E 1.0 is evaluated through benchmarks, e.g., CASC-26 (2017) and CASC-J9 (2018) competition problems (FOFdivision). Experimental results show that C S E _ E 1.0 indeed enhances the performance of E to a certain extent.


2015 ◽  
Vol 6 (6) ◽  
pp. 733-740 ◽  
Author(s):  
Victor Toporkov ◽  
Anna Toporkova ◽  
Alexey Tselishchev ◽  
Dmitry Yemelyanov ◽  
Petr Potekhin

2021 ◽  
pp. 2796-2812
Author(s):  
Nishath Ansari

     Feature selection, a method of dimensionality reduction, is nothing but collecting a range of appropriate feature subsets from the total number of features. In this paper, a point by point explanation review about the feature selection in this segment preferred affairs and its appraisal techniques are discussed. I will initiate my conversation with a straightforward approach so that we consider taking care of features and preferred issues depending upon meta-heuristic strategy. These techniques help in obtaining the best highlight subsets. Thereafter, this paper discusses some system models that drive naturally from the environment are discussed and calculations are performed so that we can take care of the preferred feature matters in complex and massive data. Here, furthermore, I discuss algorithms like the genetic algorithm (GA), the Non-Dominated Sorting Genetic Algorithm (NSGA-II), Particle Swarm Optimization (PSO), and some other meta-heuristic strategies for considering the provisional separation of issues. A comparison of these algorithms has been performed; the results show that the feature selection technique benefits machine learning algorithms by improving the performance of the algorithm. This paper also presents various real-world applications of using feature selection.


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