A Neutrosophic Information-Fusion Framework for

Renewable-Energy Site Selection under Conflicting

Sustainability Criteria

Abudulkadir Shermatov1,* Safina Tashabayeva2

1 Almaty Institute of Technology, Almaty, Kazakhstan

2 Youth Organization of Technology, Almaty, Kazakhstan

Received: August 18, 2025 Accepted: November 21, 2025 ⋆ Corresponding author

ABSTRACT

Siting a solar or wind farm forces planners to reconcile criteria that disagree by nature: irradiation or wind

resource, land cost, grid proximity, ecological sensitivity and social acceptance. The evidence for each criterion is

heterogeneous and uncertain—remote-sensing estimates, cadastral records, and public-consultation sentiment—and

experts often cannot commit to a definite rating. This paper proposes a neutrosophic information-fusion framework

that encodes each expert rating as a single-valued neutrosophic number, derives objective criterion weights by

neutrosophic entropy, fuses the ratings with a single-valued neutrosophic weighted geometric operator (which,

unlike the arithmetic operator, penalises a poor score on any single criterion), and ranks candidate sites by a deneutrosophied

score. Applied to six candidate sites and seven criteria, the framework selects a site that balances a

strong resource against low ecological conflict, and a full sensitivity analysis over the weight scheme and the risk

attitude shows the choice is robust. A comparison against fuzzy-AHP and SVN-TOPSIS indicates the neutrosophic

geometric model better exposes sites whose ranking rests on contested, high-indeterminacy criteria.

Keywords: Neutrosophic sets Information fusion Site selection Renewable energy Multi-criteria decision analysis

Entropy weighting

1. INTRODUCTION

The energy transition is, in large part, a land-use problem.

Deciding where to build a solar or wind installation is a multicriteria

decision that must weigh a technical resource (how

much sun or wind) against economic factors (land and connection

cost), environmental factors (habitat and biodiversity

impact) and social factors (local acceptance). These criteria

conflict: the windiest ridge may also be the most ecologically

sensitive, and the cheapest land may be far from the grid.

Compounding the conflict is uncertainty of an unusual kind.

Resource maps come with estimation error; ecological sensitivity

is graded by experts who genuinely disagree; and social

acceptance, gauged from consultations, is often indeterminate—

neither clear support nor clear opposition. Standard

fuzzy MCDM captures gradation but not this indeterminacy.

We adopt a neutrosophic representation so that “the community

is divided” is modelled as high indeterminacy rather than

as lukewarm support, and we treat the combination of criteria

as an explicit information-fusion step.

The distinction is not academic. A site whose social acceptance

is genuinely indeterminate—half the community

strongly in favour, half strongly opposed— poses a very different

planning risk from a site that is uniformly regarded