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Record W3097761912 · doi:10.18280/ejee.224-509

A Multi-Objective Hybrid Algorithm for Planning Electrical Distribution System

2020· article· en· W3097761912 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

venuePublished in a venue whose home country is Canada.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueEuropean Journal of Electrical Engineering · 2020
Typearticle
Languageen
FieldEngineering
TopicPower Systems and Technologies
Canadian institutionsnot available
Fundersnot available
KeywordsComputer scienceDistribution (mathematics)AlgorithmMathematics

Abstract

fetched live from OpenAlex

In this manuscript we establish a multiple-objective gravitational search algorithm (GSA) and Tabu heuristic search to plan electrical distribution system. GSA is minimized the Distribution Generator (DG) investment cost, cost of distribution system loss, operation as well as DG maintenance cost with help of appropriate constraints. So the optimum sizing of DG is planned in the optimum location with reduced cost. Here, the Gravitational Search Algorithm (GSA) accelerates the speed of convergence to combination of Tabu heuristic search method search strategy. As established multipurpose hybrid algorithm to plan electrical distribution system performed at MATLAB / simulink platform as well as efficiency evaluated to compare it other methods. The outcomes of comparison determine the advantage of established method as well as confirm its potential to resolve issue.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Methods · Consensus signal: none
Teacher disagreement score0.960
Threshold uncertainty score0.833

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.013
GPT teacher head0.200
Teacher spread0.187 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it