Algorithm Analysis A Technical Report

An Improved SSPCO Optimization Algorithm for Solve of the Clustering Problem

Swarm Intelligence (SI) is an innovative artificial intelligence technique for solving complex optimization problems. Data clustering is the process of grouping data into a number of clusters. The goal of data clustering is to make the data in the same cluster share a high degree of similarity while being very dissimilar to data from other clusters. Clustering algorithms have been applied to a ...

An Improved SSPCO Optimization Algorithm for Solve of the Clustering Problem

Swarm Intelligence (SI) is an innovative artificial intelligence technique for solving complex optimization problems. Data clustering is the process of grouping data into a number of clusters. The goal of data clustering is to make the data in the same cluster share a high degree of similarity while being very dissimilar to data from other clusters. Clustering algorithms have been applied to a ...

Designing a smart algorithm for determining stock exchange signals by data mining

One of the most important problems in modern finance is finding efficient ways to summarize and visualize the stock exchange market. This research proposes a smart algorithm by means of valuable big data that is generated by stock exchange market and different kinds of methodology to present a smart model.In this paper, we investigate relationships between the data and access to their lat...

Cautious Greedy Strategy for Bearing-based Active Localization: Technical Report Cautious Greedy Strategy for Bearing-based Active Localization: Technical Report Cautious Greedy Strategy for Bearing-based Active Localization: Technical Report

We study a novel sensing model which occurs in wildlife monitoring applications. The sensor can be approximated as a bearing-to-target sensor, but with several critical attributes that set it apart from those addressed in bearingonly tracking literature. We propose a measurement strategy that can guarantee reduction in uncertainty in competitive time, regardless of the problem instance. We prov...

A Nonlinear Autoregressive Model with Exogenous Variables Neural Network for Stock Market Timing: The Candlestick Technical Analysis

In this paper, the nonlinear autoregressive model with exogenous variables as a new neural network is used for timing of the stock markets on the basis of the technical analysis of Japanese Candlestick. In this model, the “nonlinear autoregressive model with exogenous variables” is an analyzer. For a more reliable comparison, here (like the literature) two approaches of  Raw-based and Signal-ba...

Case report (Technical and scientific) of transverse excitation atmospheric air laser