Special Issue on Soft Computing for Modeling and Simulation
Notice bibliographique
Résumé
Welcome to this special issue on Soft Computing for Modeling and Simulation of the Journal of Advanced Computational Intelligence and Intelligent Informatics (JACIII). We are pleased to introduce 5 selected papers and 4 regular papers presented at NASTEC (North-American Simulation Technology Conference), which is a series of conferences initiated by Eurosis after in-depth discussions with Prof. Mokhtar Beldjehem and North-American Simulationists, Soft Computing Scientists, addressing issues regarding the interplays and synergies between Modeling, Simulation and Soft Computing. The first NASTEC 2008 was organized at Mc Gill University, Montré{e}al, Canada, which is its birth place. It has attracted Simulationists, researchers and practitioners of Soft Computing, attendees from academic, industry and government agencies in an exchange of ideas and shared experiences. The intent of the NASTEC'2008 event is to nurture the spirit of cooperation and strive to improve the quality of life in this global village through excellence in hybrid Soft Computing research and education by engineering of next-generation intelligent hybrid Soft Computing systems for Modeling, Simulation, Simulation-based and Data-driven Software Engineering, Web-centric Computing, E-learning and Virtual Reality Systems at the service and for the benefits of the humankind. Computer Simulation is being acknowledged as the “third leg” of scientific discovery and analysis, along with theory and experimentation. Simulation Technology aims at building the “software digital factory.” The fields of Modeling, Simulation, and Soft Computing in general have made significant progress; parts of them were reflected in the present Special issue. This issue was able to attract top-level and forefront research. The themes center on novel issues in connection with Modeling, Simulation, Soft Computing, Simulation-based Software Engineering, Web-centric Computing, Virtual Reality Systems, their interplays and synergies. We are grateful to a number of people without whom we would not have been able to put this special issue together. They include our NASTEC'08 IPC and JACIII reviewers for making this special issue possible; they have done an excellent job: We got 4.5 reviews per paper on the average. We are grateful to authors of selected papers who have considered JACIII as the target for their work, and even though we could not accommodate every submission in this issue, we hope that the reviews will be helpful to many people. We are also grateful to Prof. Toshio Fukuda, Nagoya University, and Prof. Kaoru Hirota, Tokyo Institute of Technology, the editors-in-chief, and the NASTEC 2008 conference staff for inviting us to guest-edit this Journal. Last, but not least, we are indebted to the staff of JACIII and Fuji Technology Press for making this a reality.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,004 | 0,010 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,003 | 0,003 |
| Bibliométrie | 0,003 | 0,002 |
| Études des sciences et des technologies | 0,002 | 0,002 |
| Communication savante | 0,009 | 0,006 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,004 | 0,008 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,159 | 0,049 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».