Predictive collaborative performance system in B2B supply chain using neuro-fuzzy
Notice bibliographique
Résumé
Recently, contemporary B2B supply chain management (B2B-SCM) has been furnished with semi-automated data record systems to gather large quantities. Notwithstanding, most of companies and academic research groups have also concentrated on the results of the historical performance measurement interpretation and relied on the things, what have already happened. These has been rarely concerned the performance inclination. It has resulted in the lack of well-rounded performance planning improvement in the long term. Moreover, they have focused on the physical operation performance enhancement without concerning the collaborative performance among their partners. On the grounds of the fact that, this paper is to present a Neuro-fuzzy system approach to construct collaborative performance which has forward looking collaborative capabilities and its linguistic rules to make understanding how to put the collaborative performance directions in another time. The methodology is as follows. Firstly, B2B-SC performance evaluation questionnaires, with two levels were able to distinguish collaborative relation between two or more partners in their SC were congregated from the case study chains. The data set of relationships between enterprise and its direct clients of the case study companies in France was used for manifestation. Secondly, data cleaning and preparations before the proposed model construction. The multi attribute decision making, simple additive weighting, was employed to build the collaborative performance scoring model, as well. Thirdly, the pervious results were use as the learning dataset to make up of the predictive collaborative performance system based on Neuro-fuzzy. Finally, the result deployment for collaborative performance guideline from model was validated by the domain experts in term of its real practical usage efficiency. The developed system enables managers to develop systematic manners to foresee future collaborative performance and recognize latent problems in their collaboration. The prognostic ability of the developed system is comparable with the decision of the manager in their collaboration. The comment on its usages and difficulties in its developed process are also discussed. Furthermore, the final predictive results and rules contain very interesting information relating to SC improvement in long runs.
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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 | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,001 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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 ».