Search · four archives
Search · four archives
18 papers · ranked by Valyu relevance
Mihai Oltean
Multi Expression Programming (MEP) is a Genetic Programming variant which encodes multiple solutions in a single chromosome. This paper introduces and deeply describes several strategies for solving binary and multi-class classification problems within the multi solutions per chromosome paradigm of MEP. Extensive…
Mihai Oltean, Crina Groşan
Finding the optimal parameter setting (i.e. the optimal population size, the optimal mutation probability, the optimal evolutionary model etc) for an Evolutionary Algorithm (EA) is a difficult task. Instead of evolving only the parameters of the algorithm we will evolve an entire EA capable of solving a particular…
Mihai Oltean
A unique MEP feature is the ability of storing multiple solutions of a problem in a single chromosome. Usually, the best solution is chosen for fitness assignment. When solving symbolic regression or classification problems (or any other problems for which the training set is known before the problem is solved) MEP has…
Najla Akram, AL-Saati, Taghreed Riyadh Alreffaee
- Estimating the effort of software systems is an essential topic in software engineering, carrying out an estimation process reliably and accurately for a software forms a vital part of the software development phases. Many researchers have utilized different methods and techniques hopping to find solutions to this…
Majid Khan, Mujahid Ali, Taoufik Najeh, Yaser Gamil
Bentonite plastic concrete (BPC) demonstrated promising potential for remedial cut-off wall construction to mitigate dam seepage, as it fulfills essential criteria for strength, stiffness, and permeability. High workability and consistency are essential attributes for BPC because it is poured into trenches using a…
Israr Ilyas, Adeel Zafar, Muhammad Faisal Javed, Furqan Farooq + 4 more
This study provides the application of a machine learning-based algorithm approach names “Multi Expression Programming” (MEP) to forecast the compressive strength of carbon fiber-reinforced polymer (CFRP) confined concrete. The suggested computational Multiphysics model is based on previously reported experimental…
Mihai Oltean
We investigate the possibility of encoding multiple solutions of a problem in a single chromosome. The best solution encoded in an individual will represent (will provide the fitness of) that individual. In order to obtain some benefits the chromosome decoding process must have the same complexity as in the case of a…
Muhammad Nasir Amin, Kaffayatullah Khan, Muhammad Faisal Javed, Dina Yehia Zakaria Ewais + 6 more
Rice husk ash (RHA) is a significant pollutant produced by agricultural sectors that cause a malignant outcome to the environment. To encourage the re-use of RHA, this work used multi expression programming (MEP) to construct an empirical model for forecasting the compressive nature of concrete made with RHA (CRHA) as…
Song Deng, Dong Yue, Le-chan Yang, Xiong Fu + 2 more
'Jayoung Kim'] For high-dimensional and massive data sets, traditional centralized gene expression programming (GEP) or improved algorithms lead to increased run-time and decreased prediction accuracy. To solve this problem, this paper proposes a new improved algorithm called distributed function mining for gene…
Danila Bredikhin, Ilia Kats, Oliver Stegle
Advances in multi-omics technologies have led to an explosion of multimodal datasets to address questions ranging from basic biology to translation. While these rich data provide major opportunities for discovery, they also come with data management and analysis challenges, thus motivating the development of tailored…
Zhuang Yu, Haijiao Lu, Hongzong Si, Shihai Liu + 7 more
GEP is an evolutionary algorithm introduced by Ferreira in 2001. It can emulate biological evolution based on computer programming. With the assumption of being, in some way, a natural development of genetic programming (GP) preserves few properties of genetic algorithms (GA). The GEP algorithm inherits the advantages…
Charalampos P. Triantafyllidis, Lazaros G. Papageorgiou, Marian Gheorghe
'Marian Gheorghe'] This paper presents a novel prototype platform that uses the same LaTeX mark-up language, commonly used to typeset mathematical content, as an input language for modeling optimization problems of various classes. The platform converts the LaTeX model into a formal Algebraic Modeling Language (AML)…
Zhihao Lai, Sarena F. Flanigan, Marion Boudes, Chen Davidovich
Recombinant macromolecular complexes are often produced by the baculovirus system, using multigene expression vectors. Yet, the construction of baculovirus-compatible multigene expression vectors is complicated and time-consuming. Furthermore, while the baculovirus and yeast are popular protein expression systems, no…
Federico Ciccozzi
To manage the rapidly growing complexity of software development, abstraction and automation have been recognised as powerful means. Among the techniques pushing for them, model-driven engineering has gained increasing attention from industry for, among others, the possibility to automatically generate code from…
Authors not listed
Deriving versatile and robust mechanistic models from experimental data is a key challenge in engineering and natural sciences. This is especially true in chemical reaction engineering, where reactor manufacturers and operators increasingly pursue the development and maintenance of digital twins that rely on frequent…
Authors not listed
Curried functions provide a systematic way of transforming multi-argument functions into nested singleargument functions. This transformation allows partial application and supports many central principles of functional programming. Their extension, called curried 𝑘-ary functions, naturally generalizes the familiar…
Authors not listed
Automated chemistry platforms hold the potential to enable large-scale organic synthesis campaigns, such as producing a library of compounds for biological evaluation. The efficiency of such platforms will depend on the schedule according to which the synthesis operations are executed. In this work, we study the…
Andreea-Ingrid Funie, Paul Grigoras, Pavel Burovskiy, Wayne Luk + 1 more
'Mark Salmon'] Genetic programming can be used to identify complex patterns in financial markets which may lead to more advanced trading strategies. However, the computationally intensive nature of genetic programming makes it difficult to apply to real world problems, particularly in real-time constrained scenarios.…