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1st International Symposium on Physics and Applications, ISPA 2020

作者： Munawaroh, F. Muharrami, L.K. Triwikantoro Arifin, Z. Natural Science Education Study Program Universitas Trunojoyo Madura Bangkalan Indonesia Department of Physics Faculty of Science and Data Analytics Institut Teknologi Sepuluh Nopember Surabaya Indonesia

The characterization and classification of purity of limestone at Madura Island was investigated. Sampling was taken from nine quarries from different areas. The chemical analysis was carried out by X-ray fluorescence (XRF);the crystalline phase was characterized by X-ray diffraction (XRD). Analysis of purity classification based on XRF and XRD results according to British Geological Survey. Limestone has different purity, there are very high, medium, low and impure purity. The sample has a very high purity from Pamekasan (P.1) with CaO content of 99.06 wt% and 100% calcite. The samples are medium purity from Bangkalan (B.1, B.3), Pamekasan (P.2), Sumenep (S.1, and S.3) with CaO content of 91.61- 93.67 wt%. The samples are low purity from S.2 with CaO content 85.79 wt% and 100% dolomite. And the sample has impurities from P.3 and B.2 with CaO content 82.3 wt% and 84.7 wt%. Limestone with very high and medium purity which is processed into PCC can be applied in many industries as filler in rubber, paper making, plastic, paint, food, pharmaceutical, ceramic, adhesives, sealants, agriculture, and animal feed. © Published under licence by IOP Publishing Ltd.

关键词： Limestone

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Fitness Landscape Optimization Makes Stochastic Symbolic Search By Genetic programming Easier

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IEEE Transactions on Evolutionary Computation 2024年

作者： Huang, Zhixing Mei, Yi Zhang, Fangfang Zhang, Mengjie Banzhaf, Wolfgang Victoria University of Wellington Centre for Data Science and Artificial Intelligence School of Engineering and Computer Science Wellington6140 New Zealand Michigan State University BEACON Center for the Study of Evolution in Action and Ecology Evolution and Behavior Program Department of Computer Science and Engineering East LansingMI48864 United States

Searching for symbolic models plays an important role in a wide range of domains such as neural architecture search and automatic program synthesis. Genetic programming is a promising stochastic method for searching effective symbolic models within an acceptable time. The genetic programming performance is closely related to the hardness of the fitness landscape. A better fitness landscape with less local optima normally implies that it is easier to search for better solutions. In recent years, there have been many studies enhancing genetic programming performance by forming better fitness landscapes. However, the better design of the fitness landscape highly relies on specific domain knowledge and consumes a lot of expert effort. This paper proposes a fitness landscape optimization method to automatically design better fitness landscapes for genetic programming search than the manually designed ones. We optimize the landscapes by optimizing the neighborhood structures of symbolic solutions. We verify the effectiveness of the proposed method in both supervised learning and combinatorial optimization problems. The results show that the proposed method significantly reduces the hardness of fitness landscapes. By simply searching against the automatically optimized fitness landscapes, a genetic programming method can have a very competitive performance with state-of-the-art methods. © 1997-2012 IEEE.

关键词： Genetic programming

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Kohonen-SOM LOF Approach for Anomaly Detection 7

Kohonen-SOM LOF Approach for Anomaly Detection

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7th IEEE Information Technology International Seminar, ITIS 2021

作者： Muhaimin, Amri Fithriasari, Kartika Universitas Pembangunan Nasional 'Veteran' Jawa Timur Data Science Program Study Surabaya Indonesia Institut Teknologi Sepuluh Nopember Department of Statistics Surabaya Indonesia

ISBN: (纸本)9781665408073

Water loss in distribution is a serious problem for water companies, as it can result in a loss of profit. Machine learning has a method for dealing with this, for example, anomaly detection. Anomalies in the study were detected using data from March 2017 to February 2018. The data used is water consumption, and the variables such as mean water use, maximum water use, and standard deviation of water usage were obtained. Kohonen Self-Organizing Map (SOM) and Local Outlier Factor (LOF) are used because they can create a good cluster, and LOF can detect which one of them is filled with anomalies. The Kohonen SOM algorithm produced 45 groups that were considered anomalous because their silhouette width criteria were less than the group's average silhouette width. There are 45 different groups of unexpected anomalies. The LOF generated 1229 unusual consumption events, with each incident involving 579 households or customers. The frequency calculation yields 41 customers who are suspected of being anomalous. While the baseline method from the company only captures 16 anomalies out of 41 customers. This is because the company method fails to capture unusual consumption behaviors, such as monthly consumption. The anomaly detected the customer's characteristic of having an average of more than average usage of classes and sub-zones. © 2021 IEEE.

关键词： Anomaly detection

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Investigation of the hexagonal boron nitride (h-BN) electronic and structural parameters and its dependency on the known semi-local functionals 5

Investigation of the hexagonal boron nitride (h-BN) electron...

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5th Padjadjaran International Physics Symposium, PIPS 2022

作者： Tiana, W.R. Ramadhan, M.R. Astuti, F. Physics Study Program Republic of Indonesia Defense University Kawasan Indonesia Peace and Security Center Sentul Bogor16810 Indonesia Department of Physics Faculty of Science Data Analytics Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya60111 Indonesia

Known as the next wonder material after graphene, hexagonal form of Boron-Nitride (hBN) attracts a lot of interest due to its capabilities to be utilized in wide range of applications. Here we investigate bilayer structure of hBN using density functional theory (DFT) techniques. In pristine case, we observed that the SCAN functional gives a significantly better estimation of inter-layer distance compared to the PBE functional. Furthermore, we also modelled the hBN structure with a single oxygen molecule sandwiched in between of B-N layer, and conclude that the most probable sites for oxygen molecule to be trapped is at the exact center of the bilayer hBN structure. © Published under licence by IOP Publishing Ltd.

关键词： Boron nitride

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Pressure-dependent electronic properties in the rocksalt structure of lithium fluoride: A DFT study 5

Pressure-dependent electronic properties in the rocksalt str...

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5th Padjadjaran International Physics Symposium, PIPS 2022

作者： Gunawan, A.F. Astuti, F. Physics Study Program Republic of Indonesia Defense University Kawasan Indonesia Peace and Security Center Sentul Bogor16810 Indonesia Department of Physics Faculty of Science Data Analytics Institut Teknologi Sepuluh Nopember Kampus ITS Sukolilo Surabaya60111 Indonesia

Density functional theory (DFT) calculation are carried out for the cubic structure of lithium fluoride (LiF). Variation of applied pressure is considered, ranging from 0 to 120 GPa with an increment of 30 GPa based on PBE and SCAN functional scheme. In zero pressure and energy-cut off 100 Ry, best result on lattice parameter is obtained by using PBE functional with the value of 4.06 Å, while SCAN functional overestimates the lattice parameter at 4.15 Å. The insulating gap of both results is significantly underestimated with 8.82 eV and 9.26 eV for PBE and SCAN functionals respectively. With the applied hydrostatic pressure, the lattice parameter are reduced exponentially, while still retaining the insulating behaviour with an increased value of gap energy. © Published under licence by IOP Publishing Ltd.

关键词： Lattice constants

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Testing the Inference Accuracy of Accelerator-Friendly Approximate Phylogeny Tracking

Testing the Inference Accuracy of Accelerator-Friendly Appro...

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2025 IEEE Symposium on Computational Intelligence in Artificial Life and Cooperative Intelligent Systems, ALIFE-CIS 2025

作者： Moreno, Matthew Andres Ranjan, Anika Dolson, Emily Zaman, Luis University of Michigan Department of Ecology and Evolutionary Biology Ann Arbor United States Center for the Study of Complex Systems University of Michigan Ann Arbor United States Michigan Institute for Data and Ai in Society University of Michigan Ann Arbor United States Undergraduate Research Opportunities Program University of Michigan Ann Arbor United States Michigan State University Department of Computer Science and Engineering East Lansing United States Program in Ecology Evolution and Behavior Michigan State University East Lansing United States

ISBN: (纸本)9798331508371

Computer simulations are an important tool for studying the mechanics of biological evolution. In particular, agent-based approaches provide an opportunity to collect high-quality records of ancestry relationships. Such phylogenies can provide insight into evolutionary dynamics within these simulations. Previous work generally tracks lineages directly, yielding an exact phylogenetic record of evolutionary history. However, challenges exist in scaling direct ancestrytracking approaches to highly-distributed, many-processor evolution in silico. An alternative approach is to estimate phylogenetic history via noncoding annotations on digital genomes, akin to how bioinformaticians build phylogenies by assessing genetic similarities between organisms. Recent work has extended this 'hereditary stratigraphy' approach to support powerful hardware accelerator platforms, such as the Cerebras Wafer-Scale Engine. Although these second-generation 'surface'-based hereditary stratigraphy algorithms have demonstrated order-ofmagnitude speedups over first-generation 'column'-based algorithms, it remains unknown how they impact the accuracy of reconstructed phylogenies. To address this question, we assessed reconstruction accuracy under alternative configurations across a matrix of evolutionary conditions varying in selection pressure, spatial structure, and ecological dynamics. Encouragingly, we find that the second-generation approaches provide higher reconstruction quality across most surveyed conditions. © 2025 IEEE.

关键词： Biostratigraphy

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Multi-Representation Genetic programming: A Case study on Tree-based and Linear Representations

arXiv

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arXiv 2024年

作者： Huang, Zhixing Mei, Yi Zhang, Fangfang Zhang, Mengjie Banzhaf, Wolfgang Centre for Data Science and Artificial Intelligence School of Engineering and Computer Science Victoria University of Wellington Wellington6140 New Zealand Department of Computer Science and Engineering BEACON Center for the Study of Evolution in Action and Ecology Evolution and Behavior Program Michigan State University East LansingMI48864 United States

Existing genetic programming (GP) methods are typically designed based on a certain representation, such as tree-based or linear representations. These representations show various pros and cons in different domains. However, due to the complicated relationships among representation and fitness landscapes of GP, it is hard to intuitively determine which GP representation is the most suitable for solving a certain problem. Evolving programs (or models) with multiple representations simultaneously can alternatively search on different fitness landscapes since representations are highly related to the search space that essentially defines the fitness landscape. Fully using the latent synergies among different GP individual representations might be helpful for GP to search for better solutions. However, existing GP literature rarely investigates the simultaneous effective use of evolving multiple representations. To fill this gap, this paper proposes a multi-representation GP algorithm based on tree-based and linear representations, which are two commonly used GP representations. In addition, we develop a new cross-representation crossover operator to harness the interplay between tree-based and linear representations. Empirical results show that navigating the learned knowledge between basic tree-based and linear representations successfully improves the effectiveness of GP with solely tree-based or linear representation in solving symbolic regression and dynamic job shop scheduling problems. © 2024, CC BY.

关键词： Genetic programming

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An innovative model for capturing seasonal patterns of train passenger movement using exogenous variables and fuzzy time series hybridization

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Journal of Open Innovation: Technology, Market, and Complexity 2024年第1期10卷

作者： Devianto, Dodi Permana, Dony Arif, Erman Afrimayani, Afrimayani Yanuar, Ferra Maiyastri, Maiyastri Yollanda, Mutia Department of Mathematics and Data Science Universitas Andalas Padang 25156 Indonesia Department of Statistics Universitas Negeri Padang Padang 25132 Indonesia Information System Study Program Universitas Terbuka Tangerang Selatan 15418 Indonesia

Train is a popular mode of ground transportation due to the ability to accommodate a large number of passenger, save time, avoid traffic congestion, offer cost-effective fares, and provide a relatively high level of safety. These benefits contribute to an annual increase in passenger numbers, particularly during holidays and the year-end period. Consequently, it is essential for management to anticipate potential capacity constraints faced by train operators. Detecting this challenge encompasses observing train passenger count trends at the end of each year, which can be effectively analyzed using Seasonal Autoregressive Integrated Moving Average (SARIMA) model to account for seasonal effects. Train passenger surges also align with the Eid Al-Fitr holiday in Indonesia, an event that varies annually according to the Hijri calendar. To address this issue, SARIMA was adapted to include exogenous effects in the form of calendar variations, producing Seasonal Autoregressive Integrated Moving Average with Exogenous Variables (SARIMAX). Furthermore, a novel numerical model was proposed using Fuzzy Time Series Markov Chain (FTSMC). Consequently, it is vital for management to anticipate potential capacity constraints that train operators might face. This innovation was introduced through hybrid SARIMA-FTSMC and hybrid SARIMAX-FTSMC. The results showed that hybrid SARIMA-FTSMC delivered the highest accuracy level with the smallest error value, providing more precise insights into train passenger movement patterns. These modeling results also offered valuable recommendations for risk management to address capacity limitations during the Eid Al-Fitr holiday and the year-end period, enabling train operators to optimize the services effectively. © 2024 The Authors

关键词： Accuracy level Hybrid SARIMA-FTSMC Hybrid SARIMAX-FTSMC SARIMA SARIMAX Train passenger

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Trackable Agent-based Evolution Models at Wafer Scale

arXiv

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arXiv 2024年

作者： Moreno, Matthew Andres Yang, Connor Dolson, Emily Zaman, Luis Department of Ecology and Evolutionary Biology University of Michigan Ann Arbor United States Center for the Study of Complex Systems University of Michigan Ann Arbor United States Michigan Institute for Data Science University of Michigan Ann Arbor United States Undergraduate Research Opportunities Program University of Michigan Ann Arbor United States Department of Computer Science and Engineering Michigan State University East Lansing United States Program in Ecology Evolution and Behavior Michigan State University East Lansing United States

Continuing improvements in computing hardware are poised to transform capabilities for in silico modeling of cross-scale phenomena underlying major open questions in evolutionary biology and artificial life, such as transitions in individuality, eco-evolutionary dynamics, and rare evolutionary events. Emerging ML/AI-oriented hardware accelerators, like the 850,000 processor Cerebras Wafer Scale Engine (WSE), hold particular promise. However, many practical challenges remain in conducting informative evolution experiments that efficiently utilize these platforms’ large processor counts. Here, we focus on the problem of extracting phylogenetic information from agent-based evolution on the WSE platform. This goal drove significant refinements to decentralized in silico phylogenetic tracking, reported here. These improvements yield order-of-magnitude performance improvements. We also present an asynchronous island-based genetic algorithm (GA) framework for WSE hardware. Emulated and on-hardware GA benchmarks with a simple tracking-enabled agent model clock upwards of 1 million generations a minute for population sizes reaching 16 million agents. This pace enables quadrillions of agent replication events a day. We validate phylogenetic reconstructions from these trials and demonstrate their suitability for inference of underlying evolutionary conditions. In particular, we demonstrate extraction, from wafer-scale simulation, of clear phylometric signals that differentiate runs with adaptive dynamics enabled versus disabled. Together, these benchmark and validation trials reflect strong potential for highly scalable agent-based evolution simulation that is both efficient and observable. Developed capabilities will bring entirely new classes of previously intractable research questions within reach, benefiting further explorations within the evolutionary biology and artificial life communities across a variety of emerging high-performance computing platforms. Copyright © 20

关键词： Genetic algorithms

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Development of location suitability prediction for health facilities using random forest machine learning in 2030 integrating remote sensing and GIS in West Java, Indonesia

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Environmental Advances 2025年 19卷

作者： Virtriana, Riantini Ihsan, Kalingga Titon Nur Anggraini, Tania Septi Deliar, Albertus Harto, Agung Budi Riqqi, Akhmad Sakti, Anjar Dimara Remote Sensing and GIS Research Group Faculty of Earth Science and Technology Bandung Institute of Technology Bandung 40132 Indonesia Center for Remote Sensing Bandung Institute of Technology Bandung 40132 Indonesia Doctor Program in Program Study of Geodesy and Geomatic Engineering Faculty of Earth Sciences and Technology Bandung 40132 Indonesia Geographic Information Science Universitas Pendidikan Indonesia Bandung 40111 Indonesia Center for Spatial Data Infrastructure Bandung Institute of Technology Bandung 40132 Indonesia

Access to healthcare facilities is crucial in the present day. Healthcare facilities must be proportional to the population in a given area. Therefore, it is important to increase the number of healthcare facilities in regions where there is an imbalance. Proper planning and a sustainability review are necessary when determining locations for healthcare facilities. Environmental changes can affect the suitability of a location in the future. Thus, planning that can predict future suitability conditions is required to ensure that the built locations have high sustainability. This study predicts the suitability of healthcare facility locations in 2030 in West Java using remote sensing and Geographic Information System (GIS). Both static and dynamic data processed at 30×30 meter intervals across West Java will be used. Geospatial and remote sensing data are utilized in the study. Dynamic parameter extrapolation uses data from 2000 to 2018. The random forest machine learning method is employed to obtain the suitability values for healthcare facility locations using existing health facility training data in West Java. The results show changes in the suitability classes of healthcare facilities in each region from 2018 to 2030, with some areas experiencing an increase or decrease in class. This research highlights consistently suitable locations, ensuring their sustainability as healthcare facility sites. © 2024

关键词： GIS Health Facility Machine Learning Remote Sensing

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