Search results for "Data-driven"
showing 9 items of 59 documents
Data-Driven Interactive Multiobjective Optimization Using a Cluster-Based Surrogate in a Discrete Decision Space
2019
In this paper, a clustering based surrogate is proposed to be used in offline data-driven multiobjective optimization to reduce the size of the optimization problem in the decision space. The surrogate is combined with an interactive multiobjective optimization approach and it is applied to forest management planning with promising results. peerReviewed
Data-Driven Evolutionary Optimization: An Overview and Case Studies
2019
Most evolutionary optimization algorithms assume that the evaluation of the objective and constraint functions is straightforward. In solving many real-world optimization problems, however, such objective functions may not exist, instead computationally expensive numerical simulations or costly physical experiments must be performed for fitness evaluations. In more extreme cases, only historical data are available for performing optimization and no new data can be generated during optimization. Solving evolutionary optimization problems driven by data collected in simulations, physical experiments, production processes, or daily life are termed data-driven evolutionary optimization. In this…
A data-driven surrogate-assisted evolutionary algorithm applied to a many-objective blast furnace optimization problem
2017
A new data-driven reference vector-guided evolutionary algorithm has been successfully implemented to construct surrogate models for various objectives pertinent to an industrial blast furnace. A total of eight objectives have been modeled using the operational data of the furnace using 12 process variables identified through a principal component analysis and optimized simultaneously. The capability of this algorithm to handle a large number of objectives, which has been lacking earlier, results in a more efficient setting of the operational parameters of the furnace, leading to a precisely optimized hot metal production process. peerReviewed
Startup Metrics That Tech Entrepreneurs Need to Know
2020
Metrics can be used by firms to make more objective decisions based on data. Software startups in particular are characterized by the uncertain or even chaotic nature of the contexts in which they operate. Using data in the form of metrics can help software startups to make the right decisions amid uncertainty and limited resources. However, whereas conventional business metrics and software metrics have been studied in the past, metrics in the specific context of software startups have not been studied. In this chapter, we present the results of a multivocal literature review to offer you 118 metrics practitioner experts think software startups should measure. These metrics can give you id…
Data-driven Interactive Multiobjective Optimization : Challenges and a Generic Multi-agent Architecture
2020
In many decision making problems, a decision maker needs computer support in finding a good compromise between multiple conflicting objectives that need to be optimized simultaneously. Interactive multiobjective optimization methods have a lot of potential for solving such problems. However, the growth of complexity in problem formulations and the abundance of data bring new challenges to be addressed by decision makers and method developers. On the other hand, advances in the field of artificial intelligence provide opportunities in this respect. We identify challenges and propose directions of addressing them in interactive multiobjective optimization methods with the help of multiple int…
Interactive data-driven multiobjective optimization of metallurgical properties of microalloyed steels using the DESDEO framework
2023
Solving real-life data-driven multiobjective optimization problems involves many complicated challenges. These challenges include preprocessing the data, modelling the objective functions, getting a meaningful formulation of the problem, and supporting decision makers to find preferred solutions in the existence of conflicting objective functions. In this paper, we tackle the problem of optimizing the composition of microalloyed steels to get good mechanical properties such as yield strength, percentage elongation, and Charpy energy. We formulate a problem with six objective functions based on data available and support two decision makers in finding a solution that satisfies them both. To …
Connectivity Analysis in EEG Data: A Tutorial Review of the State of the Art and Emerging Trends
2023
Understanding how different areas of the human brain communicate with each other is a crucial issue in neuroscience. The concepts of structural, functional and effective connectivity have been widely exploited to describe the human connectome, consisting of brain networks, their structural connections and functional interactions. Despite high-spatial-resolution imaging techniques such as functional magnetic resonance imaging (fMRI) being widely used to map this complex network of multiple interactions, electroencephalographic (EEG) recordings claim high temporal resolution and are thus perfectly suitable to describe either spatially distributed and temporally dynamic patterns of neural acti…
Paramedia : thresholds of the social text
2017
This work is an adaptation of Gerard Genette’s theory of paratexts to social media. Paratexts are information surrounding texts, and usually helping the user to decide whether or not to consume a text. In social media, a plurality of new information surrounds texts we read every day. They are dynamic by nature and have different authors: the social platforms, like Facebook or YouTube; the authors of texts, and the users who comment and share them. This collection of four articles will debate the ethos in social media, what is an author in social media, what are the identified paratexts in selected social media websites and the limits of interpretation of paratexts in contemporary Brazilian …
The use of digital analytics for measuring and optimizing digital marketing performance
2016
Demonstrating the monetary outcomes of marketing is no longer considered a virtue but a necessity by the top management. Marketers are increasingly held accountable for their actions, yet most marketers struggle in their attempts to measure marketing performance. The emergence of digital analytics tools (e.g., Web analytics) has raised optimism of improved measurability due to its ability to track customer behavior in the digital environment. However, research lacks a clear understanding of the opportunities and limitations of digital analytics, and what it takes from an organization to make the most of its usage. The dissertation advances the knowledge in this area by investigating how ind…