Transaction Matrix Research Articles

Algorithm of Mining Association Rule Based on Matrix

Association rule mining is one of the most important techniques of data mining. Algorithms based on matrix are efficient due to only scanning the transaction database for one time. In this paper, an algorithm of association rule mining based on the compression matrix is given. It mainly compresses the transaction matrix by integrating various strategies and fleetly finds frequent itemsets. The new algorithm optimizes the known algorithms of mining association rule based on matrix given by some researchers in recent years, which greatly reduces the temporal and spatial complexity, and highly promotes the efficiency of finding frequent itemsets.

Regional input-output models and the treatment of imports in the European System of Accounts (ESA)

Input-output models are useful tools for regional science owing to their ability to capture many of the distinguishing features of a regional economy. Since input-output tables are hard to find at the regional level, many researchers adopt nonsurvey techniques to derive regional input-output tables (RIOTs). Numerous methods have been suggested and this has spawned a stream of literature comparing the relative performance of these methods. The present paper contributes to that literature by examining a largely neglected problem of nonsurvey techniques: the allocation of imports. In the European System of Accounts (ESA), there are two ways of allocating imports: inside the interindustry transactions matrix or outside. In the former case, they are allocated as imports in the sector that produces similar goods (indirect allocation). In the latter case, imported products are allocated to the sector that uses them (direct allocation). This paper shows that the choice of a nonsurvey method should depend on the way in which imports are allocated. If the nonsurvey method is not properly chosen, the results of the procedure may be misleading and implausible. The paper concludes that LQ methods are better suited for regionalising input-output tables with directly allocated imports, whereas commodity-balance methods like CHARM are better suited for regionalising input-output tables with indirectly allocated imports.

An Effective Method for Association Rule Mining based on Transactional Matrix

of this paper is to present a new method based on transactional matrix for finding association rules more efficiently. Apriori algorithm is one of the classical algorithms for finding association rules, but it has limitations of number of times database scanned is too large and number of candidate itemsets generated is large.To reduce these two limitations a new method tries to find the association rules directly from a matrix which is generated from the transactional database . Keywords— Apriori algorithm, Association rule, Frequent itemsets, Transactional matrix generated in pruning operation, by applying transaction tag method. Dongme Sun, Sheohue Teng and et.al (5) presented a new technique based on forward and reverse scan of database. It produces the frequent itemsets more efficiently if applied with certain satisfying conditions. Sixue Bai, Xinxi Dai (6) presented a method called P-matrix algorithm to generate the frequent itemsets. It is found that the P-Matrix algorithm is more efficient and fast algorithm than Apriori algorithm to generate frequent itemsets. In this paper, a new method based on transactional matrix is presented to find the association rules from the large transactional database. In this approach a transactional matrix is generated directly from the database and then frequent itemsets and support of each frequent itemset is generated directly from the transactional matrix . It is found that the new proposed approach finds the frequent itemsets more efficiently. The performance of new method is compared with that of Apriori algorithm with the help of an example.

Comparison of computational intelligence algorithms for loadability enhancement of restructured power system with FACTS devices

This paper proposes the use of computational intelligence algorithms to determine the optimal location and control of Flexible AC Transmission System (FACTS) devices to enhance the loadability of pool and hybrid models in restructured power system. Particle Swarm Optimization (PSO), Differential Evolution (DE) and Composite Differential Evolution (CoDE) algorithms are used and their performances were compared. For this study, Thyristor Controlled Series Compensator (TCSC), Static VAR Compensator (SVC) and Thyristor Controlled Phase Shifting Transformer (TCPST) are considered. This approach uses AC load flow equations with constraints on real and reactive power generations, transmission line flow, magnitude of bus voltages and FACTS device settings. For the hybrid model, bilateral transactions are modeled using secured bilateral transaction matrix utilizing the AC distribution factor with slack bus contribution. Simulations are performed on IEEE 118 bus system. Maximum loadability, computation time and convergence characteristics are compared. The results indicate that by optimal location and control of FACTS devices, DE enhances the loadability of the pool and hybrid models with less computation time and faster convergence than PSO. Further the performance of DE is improved by using its variant, CoDE. Among the three FACTS devices, TCSC gives maximum loadability than SVC and TCPST. To conclude, for enhancing the loadability of restructured power system with FACTS devices using the computational intelligence algorithm, DE with TCSC gives maximum loadability with less computational time and faster convergence. The computational effort is further reduced by using CoDE.

Secured loadability enhancement with TCSC in transmission system using computational intelligence techniques for pool and hybrid model

This paper proposes an algorithm for the optimal location and control of Flexible AC Transmission System (FACTS) devices for enhancing the loadability in transmission system using particle swarm optimization (PSO) and differential evolution (DE) for pool and hybrid model in deregulated electricity market. This approach uses AC load flow equations with the constraints on power generation, transmission line flow, magnitude of bus voltages and FACTS device settings. The bilateral transactions are modeled using secured bilateral transaction matrix utilizing AC distribution factor with the slack bus contribution. In this proposed approach, Thyristor Controlled Series Compensator (TCSC) is used. To validate the proposed approach, simulations are performed on 39 bus New England test system and IEEE 118 bus system. Comparisons are made in terms of maximum loadability, computation time and convergence characteristics. The simulation result obtained indicates that by optimal location and control of TCSC, using DE, enhances the loadability in transmission system with less computation time and faster convergence than using PSO. This comparative study concludes that by optimal location and control of TCSC, using DE will be more effective for secured loadability enhancement in transmission system of pool and hybrid model in deregulated electricity market.

Studies of Bilateral Transactions in Deregulated Environment Using Monte Carlo Simulations

As restructuring and deregulation intensify in electric power industry, electricity sellers and buyers are permitted to establish various bilateral service transactions. The key information of how much power can be transferred through network in an interconnected power system safe and secure is major criteria for companies participating in competitive environment. Hence the transactions must be assessed ahead of their scheduling in a day ahead market and hour ahead market and these must be within Available Transfer Capability (ATC) limits to avoid congestion. This paper describes the methodology of modelling the bilateral transactions using a Transaction matrix and proposes generalized linear programming formulation to solve various system operation and planning problems for bilateral demand and DC optimal power flow (DCOPF ) formulation for pool demand in pool and bilateral coordinated market model subject to steady state security constraints. Monte Carlo methods are applied for generation of random bilateral transaction matrices and assessment of relation between bilateral transactions and system security is carried out. The impact of unified power flow controller (UPFC) placed in a transmission line of the network is studied. The reduction of cost of generation and scope for additional transfer capability are achieved due to optimal UPFSC placement.

Improved Apriori Algorithm Based on Compressing Transactional Matrix Multiplication

Apriori algorithm is one of the most classical algorithm in association rules, however, the algorithm is low efficiency, such as firstly it needs to repeatedly scan the database, which spends much in I/O. Secondly, it create a large number of 2- candidate itemsets during outputting frequent 2- itemsets. Thirdly, it doesn’t cancel the useless itemsets during outputting frequent k- itemsets. In the paper, it describes an improved algorithm based on the compressed matrices which improve the efficiency during creating frequent k- itemsets on three aspects, which simply scans the database once, after compressed transactional matrix, and by multiplied matrix get the frequent item sets, which effectively improved the efficiency in mining association rules.

Mobilidade intrageracional de renda no Brasil

Este estudo busca mensurar o grau de mobilidade intrageracional de renda no Brasil e em seus diversos subgrupos populacionais, no período de 1995 a 2005. Para tanto, serão considerados a abordagem axiomática da mobilidade e o instrumental dinâmico proposto por Aebi et al. (1999). Os cálculos da matriz de transção markoviana e dos índices de mobilidade indicam que o Brasil apresenta uma baixa mobilidade intrageracional de renda, sugerindo que sua estrutura social é relativamente rígida. Constatou-se, também, importantes heterogeneidades dentro de cada subgrupo, corroborando os resultados intergeracionais apontados por Ferreira e Veloso (2006).

Influence of TCSC on social welfare and spot price - A comparative study of PSO with classical method

In this paper, Particle Swarm Optimization (PSO) based algorithm has been suggested to find optimal location and setting of Thyristor Controlled Series Compensator (TCSC) to maximize Social Benefit (SB), considering its installation cost in competitive electricity market. PSO has simultaneously optimized generators’ active powers output, generators’ bus voltages, TCSC reactance and its location. In addition, the influence of optimally located TCSC on the magnitude of real power spot price, reactive power spot price, wheeling charges and bilateral transaction matrix has been investigated. The effectiveness of the proposed approach has been tested on IEEE 6 bus system and results obtained are compared with those obtained from various classical methods. Keywords: Bilateral transaction, Particle Swarm Optimization, Social Benefit, Spot price

RAS‐ING THE TRANSACTIONS OR THE COEFFICIENTS: IT MAKES NO DIFFERENCE*

ABSTRACT The biproportional RAS technique has become one of the most important tools to update, regionalize, or balance input–output tables. In this note, we rigorously prove that the estimation of the intermediate transactions matrix yields the same results as the estimation of the input coefficients matrix or the output coefficients matrix. We also show that this does not hold for any of the other updating procedures that have been commonly proposed as an alternative to RAS.

Power-flow Model of “Sen” Transformer for Loadability Enhancement and Comparison with Unified Power-flow Controllers in Hybrid Electricity Markets

This article proposes a power-flow model of “Sen” transformer and a mixed-integer-based non-linear programming approach for its optimal location in competitive electricity markets. The system loadability has been determined for a pool, as well as hybrid electricity market, model incorporating an AC load flow-based secure bilateral transaction matrix in an optimal power-flow model. The results have also been obtained with optimally placed unified power-flow controllers and thyristor-controlled series capacitors for comparison. The proposed technique has been demonstrated on the IEEE 24-bus reliability test system.

TCOM, an innovative data structure for mining association rules among infrequent items

Association rule mining is one of the most important areas in data mining, which has received a great deal of attention. The purpose of association rule mining is the discovery of association relationships or correlations among a set of items. In this paper, we present an efficient way to find the valid association rules among the infrequent items, which is seldom mentioned and whose importance often get ignored by other researchers. We design a new data structure, called Transactional Co-Occurrence Matrix, in short TCOM, by two passing of the original transactional database. Then the occurrence count of the itemsets and valid association rules will be mined based on TCOM, which combines the advantages of both transactional oriented (horizontal) layout and item oriented (vertical) layout of the database. It turns out that any itemsets could be randomly accessed and counted without full scan of either the original database or the TCOM, which significantly improves the efficiency of the mining processes.

New secure bilateral transaction determination and study of pattern under contingencies and UPFC in competitive hybrid electricity markets

In the competitive electricity environment, the flexibility of power transactions is expected to drastically increase among the trading partners and can compromise the system security and reliability. These transactions are to be evaluated ahead of their scheduling in a day-ahead and hour-ahead market to avoid congestion and ensure their feasibility with respect to the system operating conditions. The security of the transactions has become essential in the new environment for better planning and management of competitive electricity markets. This paper proposes a new method of secure bilateral transaction determination using AC distribution factors based on the full Jacobian sensitivity and considering the impact of slack bus for pool and bilateral coordinated markets. The secure bilateral transactions have also been determined considering critical line outage contingencies cases. The bilateral transaction matrix pattern has also been determined in the presence of unified power flow controller (UPFC). The optimal location of UPFC has been determined using mixed integer non-linear programming approach. The proposed technique has been applied on IEEE 24-bus reliability test system (RTS).

New Multi-objective Optimization Problem for Secure Bilateral Transaction Determination with UPFC in Hybrid Electricity Markets

This article proposes a new multi-objective non-linear optimization problem for secure bilateral transaction determination using AC distribution factors for pool and bilateral coordinated markets. The new multi-objective optimization problem considers minimization of deviations from scheduled transactions and real power losses in the network. The bilateral transaction matrix and generation pattern has been determined in the presence of optimally located unified power-flow controller. The results have also been compared with the secure bilateral transaction determination, minimizing only deviations from the proposed transactions. The proposed technique has been applied on an IEEE 24-bus reliability test system.

New Secure Bilateral Transaction Matrix Determination Using AC Distribution Factors and Impact of TCPAR and TCSC on Its Pattern

In the competitive electricity environment, a large number of transactions are expected to be negotiated, which can compromise the system security and reliability. According to the Federal Energy Regulatory Commission (FERC) order 889, only those transactions that should be settled are within the permissible limits of available transfer capability (ATC). Therefore, it has become essential to determine secure transactions occurring in the new environment for better planning and management of open access environment. This article proposes a new method of secure bilateral transaction determination using AC distribution factors. The bilateral transaction matrix pattern has been determined in the presence of thyristor-controlled phase angle regulator (TCPAR) and thyristor-controlled series compensator (TCSC). The optimal location of TCPAR and TCSC has been determined using the mixed integer non-linear programming approach. The bilateral transaction matrix has been determined in a hybrid market model. The proposed technique has been applied on IEEE 24-bus reliability test system (RTS).

Reliability evaluation of hybrid power markets based on multiple transaction matrix and optimal transaction curtailment

A Monte Carlo simulation technique evaluates the reliability indices of restructured power systems with a hybrid market. A model for optimal transaction curtailment for a contingency state in a hybrid market is developed to incorporate the changes brought about by deregulation. The objective of the contingency optimal transaction curtailment for each individual generation company is to minimise its revenue loss. The problem is formulated as a linear programming problem and solved using an optimisation technique. Customer load curtailment, which is the basic parameter for reliability evaluation, is determined using a load-shedding philosophy which is based on the results of the optimal transaction curtailment by the genco. Supply and demand transactions of the market participants are represented by a transaction matrix. The impact of the firm and nonfirm bilateral and reserve contracts on customer reliabilities have been studied. The technique has been illustrated by application to the IEEE Reliability Test System.

Optimal Number and Location of TCSC and Loadability Enhancement in Deregulated Electricity Markets Using MINLP

This paper proposes a new method of optimal number and location of TCSC using mixed integer non-linear programming approach in the deregulated electricity markets. Optimal number and location of TCSC controller can effectively enhance system loadability and their placement is a crucial issue due to their high cost. Since, in the competitive electricity environment more and more transactions are negotiated, which can compromise the system security. Therefore, it has become essential to determine secure transactions occurring in the new environment for better planning and management. The system loadability has been determined in a hybrid market model utilizing the secure transaction matrix. The proposed technique has been tested on IEEE 24-bus reliability test system (RTS).

Optimal power transaction matrix rescheduling under multilateral open access environment

This paper addresses a new concept for determining optimal transactions between different entities in a multilateral environment while benefits of both buyer and seller entities are taken into account with respect to the rules of the system. At the same time, constraints of the network are met, which leads to an optimal power flow problem. A modified power transaction matrix is proposed for modeling the environment. The optimization method in this paper is the continuation method, which is suited for complex situations of power system studies. This complexity will become more serious when dual interaction between financial and electrical subsystems of competitive power system are taken into account. The proposed approach is tested on a typical network with satisfactory results.

An approach for evaluation of transmission costs of real power contracts in deregulated systems

This paper presents a usage-based transmission cost allocation method based on a new set of line utility factors (LUFs), which provides power transaction impact on each element of the network in deregulated power system operation. The developed LUFs relates the line flows with generation/load for a given network configuration. In this paper, a bilateral transaction contract model through a transaction matrix and line utility factors are used to evaluate cost of bilateral power contracts. The proposed method allocates the transaction costs over the participants/contracts proportional to the ratio of power flow caused by each participant/contract and the total power flows on a designated transmission line. The method has been applied on a few sample systems, and the results for sample systems and a real life EHV equivalent system are presented for illustrative purposes.

Market Model Considering Bilateral Transactions in the Deregulated Electricity Market

This paper proposes an algorithm to simulate the transactions that take place in a free market of electricity. The algorithm presented is used for Bilateral Transaction Matrix (BTM) creation assuming that a day ahead load forecast is previously known. Bids can be made by both the generation side and the demand side to determine transaction prices, then the algorithm allocates the transactions according to market rules until the demand is satisfied. This creates feasible BTMs that can be used to study system security and to find future methods to regulate bilateral transactions through market mechanisms like the application of penalties to the transactions that affect the system’s security. Results show that the proposed algorithm is a good option for electricity market analysis. The proposed algorithm provides system planners with a practical tool for data creation to further study the effects of bilateral transactions in a deregulated electricity market.