Relevant bibliographies by topics / Exploratory landscape analysis

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Exploratory landscape analysis'

Author: Grafiati
Published: 25 May 2024
Last updated: 31 July 2025

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Journal articles on the topic "Exploratory landscape analysis"

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Rosetia, Amanda, and Nor Zalina Harun. "An Exploratory Analysis of the Definition and Conceptualization of Cultural Landscape." Jurnal Kejuruteraan si6, no. 1 (2023): 17–27. http://dx.doi.org/10.17576/jkukm-2023-si6(1)-02.

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Many have analyzed “cultural landscape” and its meaning. Some recall the basics of diverse fields, such as “a cultural landscape is a landscape that has been cultivated” or “culture that dwells in a landscape.” The need to decipher “cultural landscape” has drive n research on people’s cultural views of their immediate surroundings. This study suggests cultural landscape research in South East Asia against the backdrop of emerging approaches in cultural landscape research worldwide. Thus, this essay will examine cultural dynamics arguments and hypotheses. This exploratory review and inductive q
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Lang, Ryan Dieter, and Andries Petrus Engelbrecht. "An Exploratory Landscape Analysis-Based Benchmark Suite." Algorithms 14, no. 3 (2021): 78. http://dx.doi.org/10.3390/a14030078.

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The choice of which objective functions, or benchmark problems, should be used to test an optimization algorithm is a crucial part of the algorithm selection framework. Benchmark suites that are often used in the literature have been shown to exhibit poor coverage of the problem space. Exploratory landscape analysis can be used to quantify characteristics of objective functions. However, exploratory landscape analysis measures are based on samples of the objective function, and there is a lack of work on the appropriate choice of sample size needed to produce reliable measures. This study pres
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Chang Chien, Yi-Min, Steve Carver, and Alexis Comber. "An Exploratory Analysis of Expert and Nonexpert-Based Land-Scape Aesthetics Evaluations: A Case Study from Wales." Land 10, no. 2 (2021): 192. http://dx.doi.org/10.3390/land10020192.

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The debate over the conceptual constructs of landscape aesthetics, specifically whether landscape quality is inherently related to landscape physical characteristics or is subjectively “in the eye of the beholder,” has continued for years. Solutions accommodating both the biophysical and perceptual aspects of landscapes are thus desirable for landscape planners and policymakers. In response to policy shifts that emphasise both expert and public landscape perspectives, this study investigates the relationships between formal and informal landscape evaluations. It analyses crowdsourced data desc
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Yusup, Rahmad, Hijril Ismail, and Rima Rahmaniah. "MAPPING THE LANDSCAPE OF EXPLORATORY READING: A BIBLIOMETRIC ANALYSIS." English Review: Journal of English Education 13, no. 1 (2025): 155–64. https://doi.org/10.25134/erjee.v13i1.10226.

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The exploration of reading is pivotal for enhancing comprehension, fluency, and critical thinking. Despite its importance, discrepancies persist between theoretical models and practical applications in reading education. The objective of this study is to present a thorough review of the literature on exploring reading. Articles were searched using Publish or Perish with Scopus Database. The study analyzed 147 articles from 2019-2023. The Mendeley software is utilized to resume and manage references. The researchers applied to VOSviewer to review and identify articles. Seven clusters have been
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Staniak, Mateusz, and Przemysław Biecek. "The Landscape of R Packages for Automated Exploratory Data Analysis." R Journal 11, no. 2 (2019): 347. http://dx.doi.org/10.32614/rj-2019-033.

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Sarefo, Seth, Maurice Dawson, and Mphago Banyatsang. "An exploratory analysis of the cybersecurity threat landscape for Botswana." Procedia Computer Science 219 (2023): 1012–22. http://dx.doi.org/10.1016/j.procs.2023.01.379.

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Song, Shangzhou, Shaohua Wang, Huichun Ye, and Yong Guan. "Exploratory Analysis on the Spatial Distribution and Influencing Factors of Beitang Landscape in the Shangzhuang Basin." Land 11, no. 3 (2022): 418. http://dx.doi.org/10.3390/land11030418.

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Beitang landscape is a production system and land use pattern that ancient people created to adapt to droughts and floods during a long traditional farming culture. It has a critical reference meaning for water resource use and water systems protection in modern cities. Taking the Shangzhuang Basin (China) as an example, this study used multi-source data, such as remote sensing images, Beitang vector dataset, land-use dataset, elevation, slope, river, road, and field survey, to investigate the spatial distribution and influencing factors Beitang landscape. Results showed that in a typical smal
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Munoz, Mario A., Michael Kirley, and Saman K. Halgamuge. "Exploratory Landscape Analysis of Continuous Space Optimization Problems Using Information Content." IEEE Transactions on Evolutionary Computation 19, no. 1 (2015): 74–87. http://dx.doi.org/10.1109/tevc.2014.2302006.

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Pikalov, M. V., and А. М. Pismerov. "GENETIC ALGORITHM PARAMETER TUNING USING EXPLORATORY LANDSCAPE ANALYSIS AND MACHINE LEARNING." IZVESTIYA SFedU. ENGINEERING SCIENCES, no. 2 (March 17, 2024): 221–28. http://dx.doi.org/10.18522/2311-3103-2024-2-221-228.

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Alyahya, Khulood, and Jonathan E. Rowe. "Landscape Analysis of a Class of NP-Hard Binary Packing Problems." Evolutionary Computation 27, no. 1 (2019): 47–73. http://dx.doi.org/10.1162/evco_a_00237.

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This article presents an exploratory landscape analysis of three NP-hard combinatorial optimisation problems: the number partitioning problem, the binary knapsack problem, and the quadratic binary knapsack problem. In the article, we examine empirically a number of fitness landscape properties of randomly generated instances of these problems. We believe that the studied properties give insight into the structure of the problem landscape and can be representative of the problem difficulty, in particular with respect to local search algorithms. Our work focuses on studying how these properties
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Dissertations / Theses on the topic "Exploratory landscape analysis"

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Jankovic, Anja. "Towards Online Landscape-Aware Algorithm Selection in Numerical Black-Box Optimization." Electronic Thesis or Diss., Sorbonne université, 2021. http://www.theses.fr/2021SORUS302.

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Les algorithmes d'optimisation de boîte noire (BBOA) sont conçus pour des scénarios où les formulations exactes de problèmes sont inexistantes, inaccessibles, ou trop complexes pour la résolution analytique. Les BBOA sont le seul moyen de trouver une bonne solution à un tel problème. En raison de leur applicabilité générale, les BBOA présentent des comportements différents lors de l'optimisation de différents types de problèmes. Cela donne un problème de méta-optimisation consistant à choisir l'algorithme le mieux adapté à un problème particulier, appelé problème de sélection d'algorithmes (AS
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McBride, Gemma. "An exploratory analysis of landscape-level effects on wild dog home ranges and core areas : a case study at Kosciuszko National Park, and Bago and Maragle State Forest." Master's thesis, 2007. http://hdl.handle.net/1885/132120.

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Wild dogs in Australia comprise both purebred dingoes and dingo/domestic dog hybrids. Wil d dogs are widespread across mainland Australia including the south eastern region and still maintain the role of top order predator and trophic regulator. Although they are protected in many National Parks as native species and important ecosystem regulators they are also considered to be pests in rural areas where they spread di sease and prey on small cattle and sheep. This dichotomy of perspectives can make management of the species difficult, however, with more knowledge of the behaviour and h
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Books on the topic "Exploratory landscape analysis"

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Jenset, Gard B., and Barbara McGillivray. A new methodology for quantitative historical linguistics. Oxford University Press, 2017. http://dx.doi.org/10.1093/oso/9780198718178.003.0007.

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Chapter 7 summarizes the book and discusses how the proposed framework provides researchers with the methodological guidance to answer new questions, as well as answering existing questions in new ways. A section summarizes the core steps of the quantitative research process based on the principles and best practices of Chapter 2. The importance of open data and open research processes for transparent research is highlighted. An extended case study on morphological change in early modern English is used to exemplify a research process that includes exploratory data analysis and different types
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Book chapters on the topic "Exploratory landscape analysis"

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Beham, Andreas, Erik Pitzer, Stefan Wagner, and Michael Affenzeller. "Integrating Exploratory Landscape Analysis into Metaheuristic Algorithms." In Computer Aided Systems Theory – EUROCAST 2017. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-74718-7_57.

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Mersmann, Olaf, Mike Preuss, and Heike Trautmann. "Benchmarking Evolutionary Algorithms: Towards Exploratory Landscape Analysis." In Parallel Problem Solving from Nature, PPSN XI. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-15844-5_8.

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Kerschke, Pascal, Mike Preuss, Carlos Hernández, et al. "Cell Mapping Techniques for Exploratory Landscape Analysis." In Advances in Intelligent Systems and Computing. Springer International Publishing, 2014. http://dx.doi.org/10.1007/978-3-319-07494-8_9.

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Pienaar, Johannes J., Anna S. Boman, and Katherine M. Malan. "Hilbert Curves for Efficient Exploratory Landscape Analysis Neighbourhood Sampling." In Applications of Evolutionary Computation. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-56855-8_18.

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Renau, Quentin, Carola Doerr, Johann Dreo, and Benjamin Doerr. "Exploratory Landscape Analysis is Strongly Sensitive to the Sampling Strategy." In Parallel Problem Solving from Nature – PPSN XVI. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-58115-2_10.

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Schneider, Lennart, Lennart Schäpermeier, Raphael Patrick Prager, Bernd Bischl, Heike Trautmann, and Pascal Kerschke. "HPO $$\times $$ ELA: Investigating Hyperparameter Optimization Landscapes by Means of Exploratory Landscape Analysis." In Lecture Notes in Computer Science. Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-14714-2_40.

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AbstractHyperparameter optimization (HPO) is a key component of machine learning models for achieving peak predictive performance. While numerous methods and algorithms for HPO have been proposed over the last years, little progress has been made in illuminating and examining the actual structure of these black-box optimization problems. Exploratory landscape analysis (ELA) subsumes a set of techniques that can be used to gain knowledge about properties of unknown optimization problems. In this paper, we evaluate the performance of five different black-box optimizers on 30 HPO problems, which
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Prager, Raphael Patrick, and Heike Trautmann. "Nullifying the Inherent Bias of Non-invariant Exploratory Landscape Analysis Features." In Applications of Evolutionary Computation. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-30229-9_27.

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Renau, Quentin, Johann Dreo, Carola Doerr, and Benjamin Doerr. "Towards Explainable Exploratory Landscape Analysis: Extreme Feature Selection for Classifying BBOB Functions." In Applications of Evolutionary Computation. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-72699-7_2.

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Färber, Michael, David Lamprecht, Johan Krause, Linn Aung, and Peter Haase. "SemOpenAlex: The Scientific Landscape in 26 Billion RDF Triples." In The Semantic Web – ISWC 2023. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-47243-5_6.

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AbstractWe present SemOpenAlex, an extensive RDF knowledge graph that contains over 26 billion triples about scientific publications and their associated entities, such as authors, institutions, journals, and concepts. SemOpenAlex is licensed under CC0, providing free and open access to the data. We offer the data through multiple channels, including RDF dump files, a SPARQL endpoint, and as a data source in the Linked Open Data cloud, complete with resolvable URIs and links to other data sources. Moreover, we provide embeddings for knowledge graph entities using high-performance computing. Se
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Winter, Bodo. "Mapping the landscape of exploratory and confirmatory data analysis in linguistics." In Data Analytics in Cognitive Linguistics. De Gruyter, 2022. http://dx.doi.org/10.1515/9783110687279-002.

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Conference papers on the topic "Exploratory landscape analysis"

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Mersmann, Olaf, Bernd Bischl, Heike Trautmann, Mike Preuss, Claus Weihs, and Günter Rudolph. "Exploratory landscape analysis." In the 13th annual conference. ACM Press, 2011. http://dx.doi.org/10.1145/2001576.2001690.

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Kerschke, Pascal, and Mike Preuss. "Exploratory landscape analysis." In GECCO '19: Genetic and Evolutionary Computation Conference. ACM, 2019. http://dx.doi.org/10.1145/3319619.3323389.

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Kerschke, Pascal, and Mike Preuss. "Exploratory landscape analysis." In GECCO '17: Genetic and Evolutionary Computation Conference. ACM, 2017. http://dx.doi.org/10.1145/3067695.3067696.

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Kerschke, Pascal, and Mike Preuss. "Exploratory Landscape Analysis." In GECCO '23 Companion: Companion Conference on Genetic and Evolutionary Computation. ACM, 2023. http://dx.doi.org/10.1145/3583133.3595058.

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Pikalov, Maxim, and Aleksei Pismerov. "Exploratory Landscape Analysis Based Parameter Control." In GECCO '23 Companion: Companion Conference on Genetic and Evolutionary Computation. ACM, 2023. http://dx.doi.org/10.1145/3583133.3596364.

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He, Yaodong, Shiu Yin Yuen, and Yang Lou. "Exploratory landscape analysis using algorithm based sampling." In GECCO '18: Genetic and Evolutionary Computation Conference. ACM, 2018. http://dx.doi.org/10.1145/3205651.3205660.

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Tanabe, Ryoji. "Towards exploratory landscape analysis for large-scale optimization." In GECCO '21: Genetic and Evolutionary Computation Conference. ACM, 2021. http://dx.doi.org/10.1145/3449639.3459300.

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Kerschke, Pascal, Mike Preuss, Simon Wessing, and Heike Trautmann. "Detecting Funnel Structures by Means of Exploratory Landscape Analysis." In GECCO '15: Genetic and Evolutionary Computation Conference. ACM, 2015. http://dx.doi.org/10.1145/2739480.2754642.

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Škvorc, Urban, Tome Eftimov, and Peter Korošec. "Using exploratory landscape analysis to visualize single-objective problems." In GECCO '20: Genetic and Evolutionary Computation Conference. ACM, 2020. http://dx.doi.org/10.1145/3377929.3397488.

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Kerschke, Pascal, Mike Preuss, Simon Wessing, and Heike Trautmann. "Low-Budget Exploratory Landscape Analysis on Multiple Peaks Models." In GECCO '16: Genetic and Evolutionary Computation Conference. ACM, 2016. http://dx.doi.org/10.1145/2908812.2908845.

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Reports on the topic "Exploratory landscape analysis"

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Wainaina, Priscilla, Eunice Gituku, and Peter Minang. An Exploratory Study of Cost-Benefit Analysis of Landscape Restoration. World Agroforestry Centre (ICRAF), 2020. http://dx.doi.org/10.5716/wp20014.pdf.

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Khieng, Sothy, Sidney Mason, and Seakleng Lim. Innovation and Entrepreneurship Ecosystem in Cambodia: The Roles of Academic Institutions. Cambodia Development Resource Institute, 2019. https://doi.org/10.64202/wp.118.201910.

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Numerous studies have identified the importance of a healthy entrepreneurial ecosystem in stimulating and sustaining innovation and entrepreneurship. Local entrepreneurial ecosystems are made up of both formal and informal institutions, which include legal, economic, institutional, political, social and cultural factors. As well as providing various supports, including funding and incubation programs, higher education institutions create a space at the soft skills level that inspires entrepreneurial spirit and influences entrepreneurial orientation. Yet, although some studies have explored the
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