The agricultural land evaluation procedure is a valuable guide for growing plants where they are best suitable, and it has a critical role in actualizing sustainable plans for providing food security for the growing population. In agricultural land suitability analysis, different multi-criteria decision-making methods are applied. The main objective of this study is to introduce the potential usage of a new multi-criteria decision-making method the Full Consistency Method (FUCOM) in agricultural land suitability analysis. The study was carried out in the northern part of the Karamenderes plain in NW Turkey. Nine land characteristics (soil texture, soil depth, organic matter content, electrical conductivity, pH, slope, drainage, CaCO 3 %, and cation exchange capacity) were used for the land evaluation study. The weighting values of the land characteristics were calculated by the FUCOM. According to the results, 223 ha (6.26%) were highly suitable, 2650 ha (74.40%) were moderately suitable, 508 ha (14.26%) were marginally suitable, and 181 ha (5.08%) were not suitable for maize cultivation. The weighted values of the parameters were also tested with Analytic Hierarchy Process (AHP) and the Best-Worst Method (BWM). There is a general compatibility between the methodologies. The data obtained from these methods showed that analysis consists of a very positive relationship with each other. The comparisons of these methodologies showed that FUCOM’s prioritization order simplicity in parameter weighting and ability to reduce the processing intensity would provide a significant contribution and advantage to the land evaluation experts and planners. It is recommended that the Full Consistent Method could be reliably used in agricultural land suitability analysis.

The aim of this paper is to define the concept of I-statistical (I-st) rough convergence of order α (0 < α ≤ 1). It proposes the concept of I-st bounded of order α. Moreover, the necessary and sufficient condition for a sequence (x_k) to be I-st bounded of order α is studied. In addition, the necessary and sufficient condition for a sequence (x_k) to be I-st convergent of order α is examined. Finally, the need for further research studies is discussed.

This paper proposes rough convergence and rough statistical convergence of a double sequence in intuitionistic fuzzy normed spaces. It then defines the rough statistical limit points and rough statistical cluster points of a double sequence in these spaces. Afterwards, this paper examines some of their basic properties. Finally, it discusses the need for further research.

In this work, processes represented by linear stochastic dynamic system are investigated and by considering optimal control problem, principle of optimality is proven. Also, for existence of optimal control and corresponding optimal trajectory, proofs of theorems of necessity and sufficiency condition are attained.