Artificial Life and Computational Intelligence Third Australasian Conference, ACALCI 2017, Geelong, VIC, Australia, January 31 - February 2, 2017, Proceedings
This book constitutes the refereed proceedings of the Third Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2017, held in Geelong, VIC, Australia, in January/February 2017. The 32 papers presented in this volume were carefully reviewed and selected from 47 submissio...
Saved in:
| Main Authors | , , |
|---|---|
| Format | eBook Book |
| Language | English |
| Published |
Cham
Springer Nature
2017
Springer Springer International Publishing AG |
| Edition | 1 |
| Series | LNCS sublibrary. SL 7, Artificial intelligence |
| Subjects | |
| Online Access | Get full text |
| ISBN | 9783319516912 3319516914 3319516906 9783319516905 |
Cover
| Abstract | This book constitutes the refereed proceedings of the Third Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2017, held in Geelong, VIC, Australia, in January/February 2017. The 32 papers presented in this volume were carefully reviewed and selected from 47 submissions. They were organized in topical sections named: artificial life and computational intelligence and optimization algorithms and applications. |
|---|---|
| AbstractList | This book constitutes the refereed proceedings of the Third Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2017, held in Geelong, VIC, Australia, in January/February 2017. The 32 papers presented in this volume were carefully reviewed and selected from 47 submissions. They were organized in topical sections named: artificial life and computational intelligence and optimization algorithms and applications. |
| Author | Hendtlass, Tim Li, Xiaodong Wagner, Markus |
| Author_xml | – sequence: 1 fullname: Wagner, Markus – sequence: 2 fullname: Li, Xiaodong – sequence: 3 fullname: Hendtlass, Tim |
| BackLink | https://cir.nii.ac.jp/crid/1130000794350715520$$DView record in CiNii |
| BookMark | eNqN0MFOAyEQAFCM1tjW_kNjTIyHGgYWWI51U7VJEy_G64ZlocVSqMtWf9-t60VPXmaYyctkmBE6CzGYEzSRIqcUJAMugZz-qQdoRHD34kAJO0dDKTAVOQe4QJOU3jDGIDgQJobobt60zjrtlJ-unDVTFeppEXf7Q6taF0PXXobWeO_WJmhziQZW-WQmP3mMXh8WL8XTbPX8uCzmq5kihGV8JmiOWa6ENprS2uqs0ozVWFW2xoC5rDWxgkustQRQVhFWy-NKlkKWV8bSMbrtB6u0NZ9pE32byg9vqhi3qfz1287e9HbfxPeDSW35zbQJbaN8ubgvOMk5Y9k_JGNCUsCdvO5lcK7U7hgBaHc5LGRGGRbAGDmyq55plZTvWLmLIa4btd-kkmXAs05_AdpUejU |
| ContentType | eBook Book |
| DBID | I4C RYH |
| DEWEY | 006 |
| DatabaseName | Casalini Torrossa eBooks Institutional Catalogue CiNii Complete |
| DatabaseTitleList | |
| DeliveryMethod | fulltext_linktorsrc |
| Discipline | Engineering Computer Science |
| EISBN | 9783319516912 3319516914 |
| Edition | 1 1st Edition 2017 |
| Editor | Hendtlass, Tim Li, Xiaodong Wagner, Markus |
| Editor_xml | – sequence: 1 fullname: Hendtlass, Tim – sequence: 2 fullname: Li, Xiaodong – sequence: 3 fullname: Wagner, Markus |
| ExternalDocumentID | 9783319516912 EBC6286554 EBC5579310 BB23196591 5416494 |
| GroupedDBID | 0D6 0DA 38. AABBV AALVI ABBVZ ABHTH ABMNI ABQUB ACDJR ADCXD AEDXK AEKFX AEZAY AGIGN AGYGE AIODD ALBAV ALMA_UNASSIGNED_HOLDINGS AZZ BATQV BBABE CVWCR CZZ I4C IEZ LDH NUC SAO SBO SWYDZ TPJZQ TSXQS Z5O Z7R Z7S Z7U Z7V Z7W Z7X Z7Y Z7Z Z81 Z82 Z83 Z84 Z85 Z87 Z88 AEJLV RYH |
| ID | FETCH-LOGICAL-a22546-738058a7cec33dfc4bc55d0abfd01069dc2f7690cc911afa25d97612f3148bef3 |
| ISBN | 9783319516912 3319516914 3319516906 9783319516905 |
| IngestDate | Tue Mar 04 07:17:24 EST 2025 Fri May 30 22:01:18 EDT 2025 Fri May 30 23:22:04 EDT 2025 Thu Jun 26 22:32:53 EDT 2025 Tue Nov 14 22:51:50 EST 2023 |
| IsPeerReviewed | false |
| IsScholarly | false |
| LCCN | 2016961325 |
| LCCallNum_Ident | Q |
| Language | English |
| LinkModel | OpenURL |
| MergedId | FETCHMERGED-LOGICAL-a22546-738058a7cec33dfc4bc55d0abfd01069dc2f7690cc911afa25d97612f3148bef3 |
| OCLC | 970378611 1183961019 |
| PQID | EBC5579310 |
| PageCount | 401 |
| ParticipantIDs | askewsholts_vlebooks_9783319516912 proquest_ebookcentral_EBC6286554 proquest_ebookcentral_EBC5579310 nii_cinii_1130000794350715520 casalini_monographs_5416494 |
| PublicationCentury | 2000 |
| PublicationDate | 2017 c2017 2016 2017-01-20 |
| PublicationDateYYYYMMDD | 2017-01-01 2016-01-01 2017-01-20 |
| PublicationDate_xml | – year: 2017 text: 2017 |
| PublicationDecade | 2010 |
| PublicationPlace | Cham |
| PublicationPlace_xml | – name: Netherlands – name: Cham |
| PublicationSeriesTitle | LNCS sublibrary. SL 7, Artificial intelligence |
| PublicationYear | 2017 2016 |
| Publisher | Springer Nature Springer Springer International Publishing AG |
| Publisher_xml | – name: Springer Nature – name: Springer – name: Springer International Publishing AG |
| SSID | ssj0001761257 |
| Score | 2.0038352 |
| Snippet | This book constitutes the refereed proceedings of the Third Australasian Conference on Artificial Life and Computational Intelligence, ACALCI 2017, held in... |
| SourceID | askewsholts proquest nii casalini |
| SourceType | Aggregation Database Publisher |
| SubjectTerms | Computational intelligence-Congresses Special computer methods |
| Subtitle | Third Australasian Conference, ACALCI 2017, Geelong, VIC, Australia, January 31 - February 2, 2017, Proceedings |
| TableOfContents | Intro -- Preface -- Organization -- Contents -- Artificial Life and Computational Intelligence -- Extending the Delaunay Triangulation Based Density Measurement to Many-Objective Optimization -- Abstract -- 1 Introduction -- 2 The Delaunay Triangulation Based Density Measurement -- 3 The NSGA-II-DT Algorithm and Its Variations -- 4 Experimental Studies -- 5 Conclusions -- References -- Emotion, Trustworthiness and Altruistic Punishment in a Tragedy of the Commons Social Dilemma -- 1 Introduction -- 2 Background -- 3 System Description -- 4 Results -- 5 Conclusion -- References -- Equity Option Strategy Discovery and Optimization Using a Memetic Algorithm -- 1 Introduction -- 2 Equity Option Overview -- 3 Memetic Algorithm Based Search -- 4 Evolutionary Algorithm Search Results -- 4.1 Maximizing Profit for a 80% Profitable Strategy -- 4.2 Maximizing Profit for a 80% Profitable Strategy While Limiting the Maximum Equity Drawdown to Less Than 10% -- 5 Conclusions -- References -- Co-Evolving Line Drawings with Hierarchical Evolution -- 1 Introduction -- 2 Methodology -- 3 Experiments -- 4 Results and Discussion -- 5 Conclusion and Future Work -- References -- Reliability Estimation of Individual Multi-target Regression Predictions -- 1 Introduction -- 2 Related Work -- 2.1 Multi-target Modeling -- 2.2 Reliability Estimation of Single-Target Predictions -- 3 Reliability Estimation of Multi-target Predictions -- 3.1 Independent Estimation for Each Target Variable -- 3.2 Aggregation of Independent Reliability Estimates -- 3.3 Generalization to Multi-target Prediction -- 4 Evaluation and Results -- 4.1 Performance with Different Predictive Models -- 4.2 Correlations with the Prediction Error -- 5 Conclusion -- References -- Feedback Modulated Attention Within a Predictive Framework -- 1 Introduction -- 2 Related Work -- 3 Temporal Pooler Plus Attention 4.2 Further Analyses -- 5 Conclusions and Future Work -- References -- Surrogate-Assisted Multi-swarm Particle Swarm Optimization of Morphing Airfoils -- 1 Introduction -- 2 Geometrical Parametrization -- 3 Surrogate Model -- 3.1 Kriging Method -- 4 Particle Swarm Optimization -- 4.1 Optimization in a Dynamic Environment -- 5 Implementation of the Surrogate Model -- 6 Application -- 7 Results -- 8 Conclusion -- References -- Applying Dependency Patterns in Causal Discovery of Latent Variable Models -- 1 Introduction -- 1.1 Causal Bayesian Networks -- 1.2 Latent Variable Discovery -- 2 Triggers in Latent Variable Discovery -- 3 Generating Simulated Datasets of Triggers -- 4 Learning Triggers by FCI and PC Algorithms -- 5 Causal MML (CaMML) -- 6 Applying Triggers in CaMML -- 7 Conclusion -- References -- An Evolutionary Multi-criteria Journey Planning Algorithm for Multimodal Transportation Networks -- 1 Introduction -- 2 Preliminaries -- 3 Prior Work -- 4 Problem Formulation -- 4.1 Input Network -- 4.2 Weight Assignment Strategies -- 5 Proposed Method -- 5.1 Personalized Multi-criteria Genetic Algorithm (PMGA) -- 5.2 Basic Operators of the Proposed Algorithm -- 6 Experiment -- 6.1 Quality Indicators -- 6.2 Experimentation Results and Discussion -- 7 Conclusion -- References -- Estimating Passenger Preferences Using Implicit Relevance Feedback for Personalized Journey Planning -- 1 Introduction -- 2 Prior Work -- 3 Problem Formulation -- 3.1 Input Network -- 3.2 Personalized Multi-criteria Journey Planning Paradigm (MCJP) -- 4 Proposed Preference Learning Method -- 4.1 Preferences Estimating -- 4.2 An Illustrative Example of Our Approach -- 5 Experiment -- 6 Conclusion -- References -- Quantitative Assessment of Heart Function: A Hybrid Mechanism for Left Ventricle Segmentation from Cine MRI Sequences -- Abstract -- 1 Introduction 2.2 An Illustrative Example for DOPUAV -- 3 Detectable Genetic Algorithms-Based Techniques -- 3.1 Change Detection Process -- 3.2 Mask Detection Process -- 4 Experimental Setup and Results -- 4.1 DetGA Variations -- 4.2 Comparing with State-of-the-Art Algorithms -- 5 Summary and Future Work -- References -- Neighbourhood Analysis: A Case Study on Google Machine Reassignment Problem -- 1 Introduction -- 2 Problem Description -- 3 Methodology -- 4 Experiments -- 5 Results -- 6 Discussion -- 7 Conclusions -- 8 Future Work -- References -- Optimisation Algorithms and Applications -- Multi-objective Optimisation with Multiple Preferred Regions -- 1 Introduction -- 2 Definitions and Basic Principles -- 3 Preferred Regions for Different MOEAs -- 3.1 Ideas Adopted in pNSGAII -- 3.2 pAGE -- 4 Experimental Study -- 4.1 Experimental Setup -- 4.2 Results and Discussion -- 5 pNSGAII on Energy System Optimization Problem -- 6 Conclusions -- References -- An Adaptive Memetic Algorithm for the Architecture Optimisation Problem -- 1 Introduction -- 2 Related Work -- 3 Component Deployment -- 3.1 Reliability Estimation -- 4 Adaptive Memetic Algorithm -- 5 Experiments -- 5.1 Experimental Settings -- 5.2 Problem Instances -- 5.3 Benchmark Optimisation Algorithms -- 6 Results -- 7 Conclusion -- References -- Resource Constrained Job Scheduling with Parallel Constraint-Based ACO -- 1 Introduction -- 2 Problem Specification -- 3 CP-Beam-ACO -- 4 Parallel CP-Beam-ACO -- 4.1 Parallelized Stochastic Sampling -- 4.2 Full Parallelization -- 5 Experiments and Results -- 5.1 Comparing Speedup -- 5.2 Comparing Feasibility -- 5.3 Comparing Solution Quality -- 6 Discussion -- 7 Conclusion -- References -- An Iterated Local Search with Guided Perturbation for the Heterogeneous Fleet Vehicle Routing Problem with Time Windows and Three-Dimensional Loading Constraints -- 1 Introduction 3.1 Predicting Temporal Sequences -- 3.2 Outputting the Prediction Error -- 3.3 Attentional Filtering -- 3.4 Learning -- 4 Experiments and Analysis -- 4.1 Burst Sequences -- 4.2 Frequent Feature Sequences -- 5 Discussion -- 6 Conclusion -- References -- A Batch Infill Strategy for Computationally Expensive Optimization Problems -- 1 Introduction and Background -- 2 Proposed Approach -- 2.1 Initialization -- 2.2 Archive Update -- 2.3 Constructing/Updating Kriging Models -- 2.4 Identifying Infill Samples -- 2.5 Updating Best Solution -- 3 Numerical Experiments -- 3.1 Experimental Settings -- 3.2 Performance Metrics -- 3.3 Experimental Results -- 4 Summary and Future Work -- References -- Automatic Clustering and Summarisation of Microblogs: A Multi-subtopic Phrase Reinforcement Algorithm -- 1 Introduction -- 2 Related Work -- 3 Multi-subtopic Summarisation of Microblogging Posts -- 3.1 The Original PR Algorithm -- 3.2 The K-means Clustering Algorithm -- 3.3 The PRICE Algorithm -- 4 Experimental Evaluation -- 4.1 Data Collection and Pre-processing -- 4.2 Automatic and Manual Summarisation -- 4.3 Evaluation Metrics -- 4.4 Results -- 5 Conclusions and Future Work -- References -- Generation and Exploration of Architectural Form Using a Composite Cellular Automata -- 1 Introduction -- 2 Background -- 2.1 Computational Morphogenesis -- 2.2 Cellular Automata -- 2.3 Cellular Automata and Design -- 3 Model -- 4 Experiments -- 4.1 Methodology -- 4.2 Results -- 5 Discussion and Conclusion -- References -- Wrapper Feature Construction for Figure-Ground Image Segmentation Using Genetic Programming -- 1 Introduction -- 1.1 Goal -- 2 The Proposed Methods -- 2.1 CoevoGPMFC -- 2.2 WrapperGPSFC -- 3 Experiment Preparations -- 3.1 GP Settings -- 3.2 Datasets -- 3.3 Evaluation Measures -- 3.4 Experiment Design -- 4 Results -- 4.1 Training and Test Performance 2 Literature Review -- 2.1 Histogram-Based Methods -- 2.2 Statistical Model-Based Methods -- 2.3 Region-Based Methods -- 2.4 Graph-Based Methods -- 2.5 Deformable Model-Based Methods -- 2.6 Atlas-Based Methods -- 3 Methodology -- 4 Experimental Results -- 5 Conclusion and Future Work -- Acknowledgments -- References -- A Hybrid Feature Selection Scheme Based on Local Compactness and Global Separability for Improving Roller Bearing Diagnostic Performance -- Abstract -- 1 Introduction -- 2 Experiment Setup and Acoustic Emission Signal Acquisition -- 3 Proposed Fault Diagnosis Methodology -- 3.1 Heterogeneous Feature Extraction Models -- 3.2 Proposed HFS-LCGS Scheme -- 3.3 Fault Classification for Online Diagnosis -- 4 Experiment Results and Discussion -- 5 Conclusions -- Acknowledgments -- References -- Reliable Fault Diagnosis of Bearings Using Distance and Density Similarity on an Enhanced k-NN -- Abstract -- 1 Introduction -- 2 Proposed Methodology -- 2.1 Data Acquisition -- 2.2 Feature Extraction -- 2.3 Assign Membership Values to the Test Sample -- 2.3.1 Probability of Class Information Based on the Distance ( \alpha ) -- 2.3.2 Probability of Class Information Based on the Density ( \beta ) -- 2.3.3 Assigning Membership Values -- 2.4 Classification -- 3 Experimental Results and Analysis -- 4 Conclusions -- Acknowledgements -- References -- Towards Solving TSPN with Arbitrary Neighborhoods: A Hybrid Solution -- Abstract -- 1 Introduction -- 2 Methodology -- 3 Framework -- 4 Experiments -- 4.1 Case Studies -- 4.2 Problem Analysis -- 5 Conclusion -- Acknowledgement -- References -- Detectable Genetic Algorithms-Based Techniques for Solving Dynamic Optimisation Problem with Unknown Active Variables -- Abstract -- 1 Introduction -- 2 Dynamic Optimisation Problem with Unknown Active Variables -- 2.1 Mask Creation 2 Related Work |
| Title | Artificial Life and Computational Intelligence |
| URI | http://digital.casalini.it/9783319516912 https://cir.nii.ac.jp/crid/1130000794350715520 https://ebookcentral.proquest.com/lib/[SITE_ID]/detail.action?docID=5579310 https://ebookcentral.proquest.com/lib/[SITE_ID]/detail.action?docID=6286554 https://www.vlebooks.com/vleweb/product/openreader?id=none&isbn=9783319516912 |
| Volume | 10142 |
| hasFullText | 1 |
| inHoldings | 1 |
| isFullTextHit | |
| isPrint | |
| link | http://utb.summon.serialssolutions.com/2.0.0/link/0/eLvHCXMwnZ1Nb9MwGIAtKBd6AQaIMoYsxK0JSuI4H9zWqtM6FcRhlN4iJ7aniClIS7vDTvwH_gE_jV_C-zrORwcCwSVqLceR8jh5P_J-EPJapUKhXuomeaDdMBWem8eRciU8V0WYKM-TmO_87n10-jE82_BN373NZJds8zfFzW_zSv6HKowBV8yS_Qey3aIwAL-BLxyBMBxvKb_d37ZerAnxQW_3qtTNF4CmP0Pr21sOS202wRvllZzupU722X5NEcbj1Xw5DUxFJHSWq0sbrrtezs2E1i3SRNdWOwy4Y_60jZdg0xMwsM1ogFPalT50MrLT3z-JC5tog7lCu258ZWILNqUAY9mK1CaRQm5Ry7eba-ip8ONbnorWU7lnwTJ4BZhPdbwXSF2Y4GwWMFPxEMzbu3EMtvW948XZat070WJU0LDvYrdO1FRV6tcdk7GoP4PEAGmyrVH9ELXArFPQJqqy_EUGG8Xi_CEZYbLJI3JHVQfkQdtig9o37gEZD-pFPibfe-4UuVPgTve40yF3-pYa6nRInfbUHdowp3gbHWqJOxR4O7Sj7VDLmjKf_vj6jbaUaeDYMweEn5D1yeJ8furaJhuuCLAXghuzxOOJiAtVMCZ1EeYF59ITuZboL0hlEegYbmRRgFwUWgRcpnjbNQNLOleaPSWj6kulnhGaSJ8JnmuRKOxDECWRVCrSsdY5h1OjCXk1QJFdX5qAgDob8PKDCTlsCWXwvDaF2-uMg-UQpuGEHAG0rCjx6OO3WFByU9D5QVXmPPAmhLY4M7O6jXHOFrM55yCM_D9OaRK1w-d_ucohud9v8BdktL3aqSNQTrf5S7tFfwKg2IXz |
| linkProvider | Library Specific Holdings |
| openUrl | ctx_ver=Z39.88-2004&ctx_enc=info%3Aofi%2Fenc%3AUTF-8&rfr_id=info%3Asid%2Fsummon.serialssolutions.com&rft_val_fmt=info%3Aofi%2Ffmt%3Akev%3Amtx%3Abook&rft.genre=book&rft.title=Artificial+Life+and+Computational+Intelligence+%3A+third+Australasian+Conference%2C+ACALCI+2017%2C+Geelong%2C+VIC%2C+Australia%2C+January+31+%E2%80%93+February+2%2C+2017%2C+Proceedings&rft.au=Wagner%2C+Markus&rft.au=Li%2C+Xiaodong&rft.au=Hendtlass%2C+Tim&rft.date=2017-01-01&rft.pub=Springer&rft.isbn=9783319516905&rft.externalDocID=BB23196591 |
| thumbnail_m | http://utb.summon.serialssolutions.com/2.0.0/image/custom?url=https%3A%2F%2Fvle.dmmserver.com%2Fmedia%2F640%2F97833195%2F9783319516912.jpg |